Shape the Future of Data & AI - Architect Solutions That Scale This Jobot Job is hosted by: Robert Donohue Are you a fit? Easy Apply now by clicking the "Quick Apply" buttonand sending us your resume. Salary: $140,000 - $170,000 per year A bit about us: We're a global leader in data and AI/ML services and one of the fastest-growing companies in the modern data stack space. We partner with top cloud platforms like Snowflake, AWS, Azure, GCP, Databricks, Fivetran, Pinecone, Glean, and dbt to deliver innovative data, cloud, and machine learning solutions that help enterprises unlock the true power of their data. With a decade of 40%+ year-over-year growth, we've become a 6x Snowflake Partner of the Year () and earned accolades as an award-winning workplace in the US, LATAM, and India. We're a remote-first organization with a collaborative, casual culture that prizes autonomy, creativity, and curiosity. You'll work alongside some of the brightest minds in data engineering and AI/ML - all driven by a shared passion to solve the toughest data challenges for leading global enterprises. Why join us? Competitive Compensation: $140,000 - $190,000+ base salary (depending on experience) Remote-First: Work from anywhere in the US with occasional customer-site travel nationwide Massive Growth: Be part of a company growing 40% YOY, creating career advancement opportunities Cutting-Edge Tech: Build enterprise-scale solutions leveraging Snowflake, Databricks, AWS, GCP, Azure, Kafka, and more Award-Winning Culture: Collaborative, inclusive, and committed to professional development Learning & Development: Accelerated training, advanced certifications, and exposure to AI/ML innovation Time Off & Benefits: 4 weeks PTO, 10 paid holidays, health/dental/vision insurance, 401(k), and additional perks Job Details We're seeking a Solutions Architect who thrives at the intersection of data engineering solutions. This is a customer-facing, technical leadership role where you'll design, build, and deliver scalable cloud and data architectures for enterprise clients. What You'll Do: Design and implement end-to-end data solutions that are secure, performant, and scalable Collaborate with enterprise customers to understand their challenges and translate business needs into technical roadmaps Lead architecture discussions, conduct POCs, create roadmaps, diagrams, and solution documentation Work hands-on with modern data stack tools like Snowflake, Databricks, AWS, Azure, GCP, and streaming/integration tech (Kafka, Fivetran, dbt, Airflow) Support product adoption and services expansion by building trust with customer teams and executives Guide and mentor engineers, helping elevate their technical expertise Deliver presentations and demos that clearly communicate solutions to both technical and non-technical audiences What You Bring: 8+ years as a Solutions Architect/Data Engineer designing and implementing production-grade solutions 5+ years customer-facing experience with enterprise clients Strong proficiency in Python, Java, or Scala and advanced SQL skills Hands-on experience with Snowflake, Databricks, Redshift, or EMR and distributed/cloud data platforms (AWS, Azure, GCP) Familiarity with streaming tools (Kafka, Spark), orchestration (Airflow), and data integration technologies (Fivetran, Matillion, ADF) Excellent communication skills for collaborating with clients and presenting solutions Bachelor's degree in Computer Science or related field (or equivalent experience) Interested in hearing more? Easy Apply now by clicking the "Quick Apply" button. Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot's policy to comply with all applicable federal, state and local laws respecting consideration of unemployment status in making hiring decisions. Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance. Information collected and processed as part of your Jobot candidate profile, and any job applications, resumes, or other information you choose to submit is subject to Jobot's Privacy Policy, as well as the Jobot California Worker Privacy Notice and Jobot Notice Regarding Automated Employment Decision Tools which are available at By applying for this job, you agree to receive calls, AI-generated calls, text messages, or emails from Jobot, and/or its agents and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy here:

Lead Machine Learning Engineer (MLOps, KServe + building Kubernetes Clusters, PyTorch, TensorFlow on AWS) As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You’ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

What you’ll do in the role:

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you’ll be expected to perform many ML engineering activities, including one or more of the following:

• Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
• Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
• Use programming languages like Python, Scala, or Java.

Basic Qualifications:

• Bachelor’s degree
• At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
• At least 4 years of experience programming with Python, Scala, or Java
• At least 2 years of experience building, scaling, and optimizing ML systems

Preferred Qualifications:

• Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
• 3+ years of experience building production-ready data pipelines that feed ML models
• 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 2+ years of experience developing performant, resilient, and maintainable code
• 2+ years of experience with data gathering and preparation for ML models
• 2+ years of people leader experience
• 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents

At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer
McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer
New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer
Richmond, VA: $179,400 - $204,700 for Lead Machine Learning Engineer
San Jose, CA: $215,200 - $245,600 for Lead Machine Learning Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You’ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

What you’ll do in the role:

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you’ll be expected to perform many ML engineering activities, including one or more of the following:

• Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
• Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
• Use programming languages like Python, Scala, or Java.

Basic Qualifications:

• Bachelor’s Degree
• At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)
• At least 3 years of experience designing and building data-intensive solutions using distributed computing
• At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)
• At least 1 year of experience productionizing, monitoring, and maintaining models

Preferred Qualifications:

• 1+ years of experience building, scaling, and optimizing ML systems
• 1+ years of experience with data gathering and preparation for ML models
• 2+ years of experience developing performant, resilient, and maintainable code
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
• 3+ years of experience with distributed file systems or multi-node database paradigms
• Contributed to open source ML software
• Authored/co-authored a paper on a ML technique, model, or proof of concept
• 3+ years of experience building production-ready data pipelines that feed ML models
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance

At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Chicago, IL: $147,100 - $167,900 for Senior Machine Learning EngineerMcLean, VA: $161,800 - $184,600 for Senior Machine Learning EngineerPlano, TX: $147,100 - $167,900 for Senior Machine Learning EngineerRichmond, VA: $147,100 - $167,900 for Senior Machine Learning Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You’ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

What you’ll do in the role:

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you’ll be expected to perform many ML engineering activities, including one or more of the following:

• Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
• Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
• Use programming languages like Python, Scala, or Java.

Basic Qualifications:

• Bachelor’s Degree
• At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
• At least 4 years of experience programming with Python, Scala, or Java
• At least 3 years of experience building, scaling, and optimizing ML systems
• At least 2 years of experience leading teams developing ML solutions

Preferred Qualifications:

• Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 3+ years of experience developing performant, resilient, and maintainable code
• 3+ years of experience with data gathering and preparation for ML models
• 3+ years of people management experience
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
• 3+ years of experience building production-ready data pipelines that feed ML models
• Ability to communicate complex technical concepts clearly to a variety of audiences

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Sr. Lead AI Engineer (GenAI Platform) Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.

• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.

• Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.

• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

The Ideal Candidate:

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.

• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.

• You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.

• You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.

• You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies
• At least 6 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

• 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience designing, developing, integrating, delivering, and supporting complex AI systems
• Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders
• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
• Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer
McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer
New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer
San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer
San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Hands-On Principal Architect Needed for High-Growth Data Consultancy

This Jobot Job is hosted by: Robert Donohue
Are you a fit? Easy Apply now by clicking the “Apply” button and sending us your resume.
Salary: $170,000 - $225,000 per year

A bit about us:

We are a leading modern data consultancy helping enterprise clients solve their toughest data challenges through cloud, AI, analytics, and engineering solutions. Our partnerships span top platforms including Snowflake, Amazon Web Services, Microsoft Azure, Google Cloud, Databricks, Fivetran, and dbt Labs.

Our team operates in a remote-first environment across the United States, Latin America, and India. We hire top performers who thrive in a culture built on ownership, trust, innovation, and autonomy.

Recognized as an industry leader with multiple partner awards, hundreds of advanced certifications, and a reputation for delivering measurable client outcomes.

Why join us?

• Competitive Compensation: $170,000 - $225,000 base salary + Bonus
• Remote-First: Work from anywhere in the US with occasional customer-site travel nationwide
• Massive Growth: Be part of a company growing 40% YOY, creating career advancement opportunities
• Own strategic relationships and help expand enterprise accounts
• Cutting-Edge Tech: Build enterprise-scale solutions leveraging Snowflake, Databricks, AWS, GCP, Azure, Kafka, and more
• Award-Winning Culture: Collaborative, inclusive, and committed to professional development
• Learning & Development: Accelerated training, advanced certifications, and exposure to AI/ML innovation
• Time Off & Benefits: 4 weeks PTO, 10 paid holidays, health/dental/vision insurance, 401(k), and additional perks

Job Details

We are seeking a Principal Solutions Architect who can operate as both a trusted technical advisor and a strategic growth partner. This role is ideal for someone with a strong hands-on background in Data Engineering or Solutions Architecture who has also succeeded in pre-sales, post-sales, account expansion, or client consulting environments.

What You’ll Do
Client Engagement & Growth

• Build executive and stakeholder relationships within key accounts
• Understand long-term business priorities and create technical roadmaps
• Identify expansion opportunities where additional services or solutions add value
• Partner with leadership and sales teams to grow strategic accounts
• Lead responses to RFPs, RFIs, proposals, and solution presentations
• Develop compelling business cases and technical value propositions

Technical Leadership

• Architect end-to-end modern data solutions for enterprise clients
• Lead discovery sessions, assessments, proofs of concept, and solution design
• Guide implementations with focus on scalability, security, and performance
• Mentor engineers and architects across delivery teams
• Translate complex business problems into practical technical solutions

Required Background

• 8+ years in Solutions Architecture, Data Engineering, or similar client-facing technical roles
• Experience in pre-sales, post-sales, consulting, customer success engineering, or account growth
• Strong hands-on experience with cloud data platforms such as Snowflake, Databricks, Amazon Web Services, Microsoft Azure, or Google Cloud
• Strong coding skills in Python, Java, and/or Scala
• Advanced SQL optimization and data modeling skills
• Experience presenting to technical and business stakeholders
• Ability to lead technical documentation, roadmaps, and architecture artifacts
• Bachelor’s degree in Computer Science or related field

Nice to Have

• Experience with Kafka, Spark, Airflow, dbt, Fivetran, Matillion, NiFi
• Experience with streaming, lakehouse, medallion, or enterprise migration initiatives
• Prior success expanding accounts or managing strategic customers
• Cloud certifications or advanced platform credentials

Interested in hearing more? Easy Apply now by clicking the “Apply” button.

Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot’s policy to comply with all applicable federal, state and local laws respecting consideration of unemployment status in making hiring decisions.

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Lead AI Engineer, AI Foundations Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
• Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.
• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

The Ideal Candidate:

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.
• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
• You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.
• You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.
• You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
• At least 4 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

• 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience designing, developing, delivering, and supporting AI services
• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer
McLean, VA: $197,300 - $225,100 for Lead AI Engineer
New York, NY: $215,200 - $245,600 for Lead AI Engineer
San Jose, CA: $215,200 - $245,600 for Lead AI Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You’ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

Team Description: As a Lead Machine Learning Engineer in our Luxury Travel organization, you will architect the intelligent systems that power Capital One Travel’s vision for the high-end market. You’ll have the unique opportunity to transform complex data into bespoke, anticipatory experiences for our most discerning travelers. If you are a visionary technologist who thrives at the intersection of cutting-edge AI and human-centric design, and you’re driven to redefine the gold standard of travel through innovation, this is the perfect role for you.

What you’ll do in the role:

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you’ll be expected to perform many ML engineering activities, including one or more of the following:

• Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams
• Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications
• Retrain, maintain, and monitor models in production
• Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code
• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI
• Use programming languages like Python, Scala, or Java

Basic Qualifications:

• Bachelor’s Degree
• At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
• At least 4 years of experience programming with Python, Scala, or Java
• At least 2 years of experience building, scaling, and optimizing ML systems

Preferred Qualifications:

• Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
• 3+ years of experience building production-ready data pipelines that feed ML models
• 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 2+ years of experience developing performant, resilient, and maintainable code
• 2+ years of experience with data gathering and preparation for ML models
• 2+ years of people leader experience
• 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
• Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion

At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Chicago, IL: $179,400 - $204,700 for Lead Machine Learning EngineerNew York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Distinguished AI Engineer Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.

• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.

• Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.

• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

The Ideal Candidate:

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.

• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.

• You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.

• You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.

• You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies
• At least 8 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

• 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems
• Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level
• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
• Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer
McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer
New York, NY: $293,600 - $335,100 for Distinguished AI Engineer
Richmond, VA: $244,700 - $279,200 for Distinguished AI Engineer
San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer
San Jose, CA: $293,600 - $335,100 for Distinguished AI Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Lead AI Engineer (Gen AI Platform Services) Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.

• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.

• Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.

• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

The Ideal Candidate:

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.

• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.

• You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.

• You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.

• You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
• At least 4 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

• 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience designing, developing, delivering, and supporting AI services
• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

New York, NY: $215,200 - $245,600 for Lead AI Engineer
San Jose, CA: $215,200 - $245,600 for Lead AI Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Lead AI Engineer, AI Foundations Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.

• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.

• Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.

• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

The Ideal Candidate:

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.

• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.

• You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.

• You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.

• You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies
• At least 6 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

• 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience designing, developing, integrating, delivering, and supporting complex AI systems
• Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders
• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
• Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer
McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer
New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer
San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Sr. Distinguished AI Engineer (Agentic AI Platform) Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
• You will contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi-tenant policy enforcement.
• A major emphasis is around standardizing and automating agentic workflows : you will evaluate agentic frameworks such LangGraph, AutoGen, Semantic Kernal, CrewAI and LlamaIndex and then harden / blend patterns that best meet enterprise SLAs do that 90% of new apps adopt them.
• Developer experience is another cornerstone. You will contribute to crafting an end to end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes, shrinking prototyping to production timelines by 30%.
• Trust and safety remain paramount; you will help bring together a vision of central guardrail services - prompt firewalls, content-filter hooks, red team harnesses and audit APIs - consumed by every application to ensure zero Sev4 incidents.
• You will collaborate with cross organization architects to drive end to end performance by optimizing orchestration - level batching, retrieval caching, heuristic tuning to achieve reductions in per token spend. You will accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG.
• You’ll own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs
• Finally you will coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences - to amplify platform vision across internal and external communities.

The Ideal Candidate:

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.
• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
• You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.
• You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.
• You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or AI plus at least 10 years of experience developing AI and ML algorithms or technologies, or Master’s degree plus at least 8 years of experience developing AI and ML algorithms or technologies
• At least 10 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

• 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• 2+ years of experience supporting Agentic Frameworks (LangChain, CrewAI, Semantic Kernel (Microsoft), or AutoGen)
• 2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning)
• 8+ years of experience designing mission-critical machine learning platforms
• 2+ years of experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems
• Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level
• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
• Master’s degree in Computer Science, Computer Engineering, or relevant technical field
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers
• Experience leading GenAI or LLM-Powered application architectures in production
• Deep understanding of Responsible AI, data privacy and multi-tenant security patterns
• K8s mastery (multi-region clusters, service mesh)
• Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $314,800 - $359,300 for Sr. Distinguished AI Engineer
Cambridge, MA: $314,800 - $359,300 for Sr. Distinguished AI Engineer
New York, NY: $343,400 - $392,000 for Sr. Distinguished AI Engineer
San Francisco, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer
San Jose, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . click apply for full job details

Lead AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.

• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.

• Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.

• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

The Ideal Candidate:

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.

• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.

• You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.

• You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.

• You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
• At least 4 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

• 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience designing, developing, delivering, and supporting AI services
• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer
McLean, VA: $197,300 - $225,100 for Lead AI Engineer
New York, NY: $215,200 - $245,600 for Lead AI Engineer
San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer
San Jose, CA: $215,200 - $245,600 for Lead AI Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Distinguished AI Engineer Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

• You will play a crucial role to architect and launch conversational experiences that are powered by state of art Generative AI capabilities to millions of Capital One customers
• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
• Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.
• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

The Ideal Candidate:

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.
• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
• You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.
• You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.
• You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master’s degree plus at least 6 years of experience developing AI and ML algorithms or technologies
• At least 8 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

• 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems
• Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level
• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
• Master’s degree in Computer Science, Computer Engineering, or relevant technical field
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Passion for staying on top of the latest AI research and AI systems, and judiciously apply novel techniques in production
• Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer
McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer
New York, NY: $293,600 - $335,100 for Distinguished AI Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You’ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

What you’ll do in the role:

• The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you’ll be expected to perform many ML engineering activities, including one or more of the following:
• Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
• Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
• Use programming languages like Python, Scala, or Java.

Basic Qualifications:

• Bachelor’s degree
• At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
• At least 4 years of experience programming with Python, Scala, or Java
• At least 2 years of experience building, scaling, and optimizing ML systems

Preferred Qualifications:

• Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
• 3+ years of experience building production-ready data pipelines that feed ML models
• 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 2+ years of experience developing performant, resilient, and maintainable code
• 2+ years of experience with data gathering and preparation for ML models
• 2+ years of people leader experience
• 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents

At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $197,300 - $225,100 for Lead Machine Learning EngineerNew York, NY: $215,200 - $245,600 for Lead Machine Learning EngineerPlano, TX: $179,400 - $204,700 for Lead Machine Learning Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You’ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

What you’ll do in the role:

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you’ll be expected to perform many ML engineering activities, including one or more of the following:

• Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
• Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
• Use programming languages like Python, Scala, or Java.

Basic Qualifications:

• Bachelor’s Degree
• At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
• At least 4 years of experience programming with Python, Scala, or Java
• At least 2 years of experience building, scaling, and optimizing ML systems

Preferred Qualifications:

• Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
• 3+ years of experience building production-ready data pipelines that feed ML models
• 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 2+ years of experience developing performant, resilient, and maintainable code
• 2+ years of experience with data gathering and preparation for ML models
• 2+ years of people leader experience
• 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents

At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Sr. Lead AI Engineer (AI Foundations) Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
• Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.
• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

The Ideal Candidate:

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.
• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
• You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.
• You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.
• You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies
• At least 6 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

• 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience designing, developing, integrating, delivering, and supporting complex AI systems
• Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders
• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
• Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer
New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer
Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer
San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You’ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

What you’ll do in the role:

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you’ll be expected to perform many ML engineering activities, including one or more of the following:

• Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
• Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
• Use programming languages like Python, Scala, or Java.

Basic Qualifications:

• Bachelor’s Degree
• At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
• At least 4 years of experience programming with Python, Scala, or Java
• At least 3 years of experience building, scaling, and optimizing ML systems
• At least 2 years of experience leading teams developing ML solutions

Preferred Qualifications:

• Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 3+ years of experience developing performant, resilient, and maintainable code
• 3+ years of experience with data gathering and preparation for ML models
• 3+ years of people management experience
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
• 3+ years of experience building production-ready data pipelines that feed ML models
• Ability to communicate complex technical concepts clearly to a variety of audiences

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Distinguished Engineer, AI Compute (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Capital One machine learning platform organization manages our cloud-based enterprise AI+ML system delivering the high-scale developer and runtime environments required to build, orchestrate, and deploy compute and data intensive AI systems across real-time and batch workloads. We are seeking a Senior Distinguished Engineer, a hands-on technical leader passionate about distributed systems, to engineer and scale foundational compute capabilities for our platform.

You will use your experience in building large scale, highly available and high performance systems to develop our common compute infrastructure on top of CPU and GPU substrates. Your contributions will power everything from developer notebooks to ML / DL model training, model inference and feature generation pipelines to pre-training and fine tuning Transformer-based models as well as generative AI inference and agentic applications. Your depth of expertise in technologies including Golang and Python programming languages, popular distributed compute frameworks including Spark / Dask / Ray / Flink, container (e.g., Kubernetes) and serverless (e.g., AWS Lambda) runtime environments, and ML+AI workload patterns will provide an amplifying technical element that is paramount to our team’s success.

In this role, you will :

• Architect and build control and data plane implementations required to realize a highly available, multi-tenant, large scale and a secure machine learning platform
• Develop Ray and Spark distributed compute engine solutions to accelerate diverse workloads from LLM pre-training and reinforcement learning to large-scale data processing, while maximizing compute unit economics
• Engineer systemic improvements for operational excellence including automating KTLO (Keep The Lights On) workflows
• Direct the technical execution of a diverse project portfolio, collaborating with developers specializing in everything ranging from distributed microservices to running large foundation models
• Work cross-functionally with product and program management disciplines, and stakeholder and partners across Capital One to help optimize business outcomes while driving towards strong technology solutions
• Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and leading system design and code review sessions
• Help elevate the Capital One Distinguished Engineering community and establish yourself as a go-to resource on given technologies and technology-enabled capabilities
• Lead the way in creating next-generation talent, mentoring internal talent and actively recruiting external talent to bolster the Capital One tech talent pool

Capital One is open to hiring a Remote Employee for this opportunity

Basic Qualifications:

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies
• At least 10 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications :

• Master’s Degree in Computer Science or a Master’s Degree in Software Engineering
• Hands on experience in the internals of Ray (Actors/GCS/Scheduling) or Spark (Query Optimizer/Memory Management)
• Experience building platforms that support LLM training, fine-tuning, or high-throughput inference
• Hands-on experience with AWS-specific compute primitives (EKS, EC2 UltraClusters, Graviton) and cost-optimization strategies
• History of upstream contributions to major distributed systems projects

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Remote (Regardless of Location): $286,200 - $326,700 for Sr. Distinguished AI Engineer
Cambridge, MA: $314,800 - $359,300 for Sr. Distinguished AI Engineer
McLean, VA: $314,800 - $359,300 for Sr. Distinguished AI Engineer
New York, NY: $343,400 - $392,000 for Sr. Distinguished AI Engineer
Richmond, VA: $286,200 - $326,700 for Sr. Distinguished AI Engineer
San Francisco, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer
San Jose, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Shape the Future of Data & AI - Architect Solutions That Scale

This Jobot Job is hosted by: Robert Donohue
Are you a fit? Easy Apply now by clicking the “Apply” button and sending us your resume.
Salary: $140,000 - $160,000 per year

A bit about us:

We’re a global leader in data and AI/ML services and one of the fastest-growing companies in the modern data stack space. We partner with top cloud platforms like Snowflake, AWS, Azure, GCP, Databricks, Fivetran, Pinecone, Glean, and dbt to deliver innovative data, cloud, and machine learning solutions that help enterprises unlock the true power of their data.

With a decade of 40%+ year-over-year growth, we’ve become a 6x Snowflake Partner of the Year () and earned accolades as an award-winning workplace in the US, LATAM, and India.

We’re a remote-first organization with a collaborative, casual culture that prizes autonomy, creativity, and curiosity. You’ll work alongside some of the brightest minds in data engineering and AI/ML - all driven by a shared passion to solve the toughest data challenges for leading global enterprises.

Why join us?

• Competitive Compensation: $140,000 - $190,000+ base salary (depending on experience)
• Remote-First: Work from anywhere in the US with occasional customer-site travel nationwide
• Massive Growth: Be part of a company growing 40% YOY, creating career advancement opportunities
• Cutting-Edge Tech: Build enterprise-scale solutions leveraging Snowflake, Databricks, AWS, GCP, Azure, Kafka, and more
• Award-Winning Culture: Collaborative, inclusive, and committed to professional development
• Learning & Development: Accelerated training, advanced certifications, and exposure to AI/ML innovation
• Time Off & Benefits: 4 weeks PTO, 10 paid holidays, health/dental/vision insurance, 401(k), and additional perks

Job Details

We’re seeking a Solutions Architect who thrives at the intersection of data engineering and AI/ML solutions. This is a customer-facing, technical leadership role where you’ll design, build, and deliver scalable cloud and data architectures for enterprise clients.

What You’ll Do:

• Design and implement end-to-end data and AI/ML solutions that are secure, performant, and scalable
• Collaborate with enterprise customers to understand their challenges and translate business needs into technical roadmaps
• Lead architecture discussions, conduct POCs, create roadmaps, diagrams, and solution documentation
• Work hands-on with modern data stack tools like Snowflake, Databricks, AWS, Azure, GCP, and streaming/integration tech (Kafka, Fivetran, dbt, Airflow)
• Support product adoption and services expansion by building trust with customer teams and executives
• Guide and mentor engineers, helping elevate their technical expertise
• Deliver presentations and demos that clearly communicate solutions to both technical and non-technical audiences

What You Bring:

• 8+ years as a Solutions Architect/Data Engineer designing and implementing production-grade solutions
• 5+ years customer-facing experience with enterprise clients
• Strong proficiency in Python, Java, or Scala and advanced SQL skills
• Hands-on experience with Snowflake, Databricks, Redshift, or EMR and distributed/cloud data platforms (AWS, Azure, GCP)
• Familiarity with streaming tools (Kafka, Spark), orchestration (Airflow), and data integration technologies (Fivetran, Matillion, ADF)
• Excellent communication skills for collaborating with clients and presenting solutions
• Bachelor’s degree in Computer Science or related field (or equivalent experience)

Interested in hearing more? Easy Apply now by clicking the “Apply” button.

Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot’s policy to comply with all applicable federal, state and local laws respecting consideration of unemployment status in making hiring decisions.

Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance.

Information collected and processed as part of your Jobot candidate profile, and any job applications, resumes, or other information you choose to submit is subject to Jobot’s Privacy Policy, as well as the Jobot California Worker Privacy Notice and Jobot Notice Regarding Automated Employment Decision Tools which are available at

By applying for this job, you agree to receive calls, AI-generated calls, text messages, or emails from Jobot, and/or its agents and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy here:

Shape the Future of Data & AI - Architect Solutions That Scale

This Jobot Job is hosted by: Robert Donohue
Are you a fit? Easy Apply now by clicking the “Apply” button and sending us your resume.
Salary: $140,000 - $160,000 per year

A bit about us:

We’re a global leader in data and AI/ML services and one of the fastest-growing companies in the modern data stack space. We partner with top cloud platforms like Snowflake, AWS, Azure, GCP, Databricks, Fivetran, Pinecone, Glean, and dbt to deliver innovative data, cloud, and machine learning solutions that help enterprises unlock the true power of their data.

With a decade of 40%+ year-over-year growth, we’ve become a 6x Snowflake Partner of the Year () and earned accolades as an award-winning workplace in the US, LATAM, and India.

We’re a remote-first organization with a collaborative, casual culture that prizes autonomy, creativity, and curiosity. You’ll work alongside some of the brightest minds in data engineering and AI/ML - all driven by a shared passion to solve the toughest data challenges for leading global enterprises.

Why join us?

• Competitive Compensation: $140,000 - $190,000+ base salary (depending on experience)
• Remote-First: Work from anywhere in the US with occasional customer-site travel nationwide
• Massive Growth: Be part of a company growing 40% YOY, creating career advancement opportunities
• Cutting-Edge Tech: Build enterprise-scale solutions leveraging Snowflake, Databricks, AWS, GCP, Azure, Kafka, and more
• Award-Winning Culture: Collaborative, inclusive, and committed to professional development
• Learning & Development: Accelerated training, advanced certifications, and exposure to AI/ML innovation
• Time Off & Benefits: 4 weeks PTO, 10 paid holidays, health/dental/vision insurance, 401(k), and additional perks

Job Details

We’re seeking a Solutions Architect who thrives at the intersection of data engineering and AI/ML solutions. This is a customer-facing, technical leadership role where you’ll design, build, and deliver scalable cloud and data architectures for enterprise clients.

What You’ll Do:

• Design and implement end-to-end data and AI/ML solutions that are secure, performant, and scalable
• Collaborate with enterprise customers to understand their challenges and translate business needs into technical roadmaps
• Lead architecture discussions, conduct POCs, create roadmaps, diagrams, and solution documentation
• Work hands-on with modern data stack tools like Snowflake, Databricks, AWS, Azure, GCP, and streaming/integration tech (Kafka, Fivetran, dbt, Airflow)
• Support product adoption and services expansion by building trust with customer teams and executives
• Guide and mentor engineers, helping elevate their technical expertise
• Deliver presentations and demos that clearly communicate solutions to both technical and non-technical audiences

What You Bring:

• 8+ years as a Solutions Architect/Data Engineer designing and implementing production-grade solutions
• 5+ years customer-facing experience with enterprise clients
• Strong proficiency in Python, Java, or Scala and advanced SQL skills
• Hands-on experience with Snowflake, Databricks, Redshift, or EMR and distributed/cloud data platforms (AWS, Azure, GCP)
• Familiarity with streaming tools (Kafka, Spark), orchestration (Airflow), and data integration technologies (Fivetran, Matillion, ADF)
• Excellent communication skills for collaborating with clients and presenting solutions
• Bachelor’s degree in Computer Science or related field (or equivalent experience)

Interested in hearing more? Easy Apply now by clicking the “Apply” button.

Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot’s policy to comply with all applicable federal, state and local laws respecting consideration of unemployment status in making hiring decisions.

Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance.

Information collected and processed as part of your Jobot candidate profile, and any job applications, resumes, or other information you choose to submit is subject to Jobot’s Privacy Policy, as well as the Jobot California Worker Privacy Notice and Jobot Notice Regarding Automated Employment Decision Tools which are available at

By applying for this job, you agree to receive calls, AI-generated calls, text messages, or emails from Jobot, and/or its agents and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy here: