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Data Engineering Solutions Architect

Jobot

Multiple locations

Join the fastest growing Data engineering solutions company! This Jobot Job is hosted by: Adam Bennett Are you a fit? Easy Apply now by clicking the "Quick Apply" buttonand sending us your resume. Salary: $150,000 - $220,000 per year A bit about us: This is one of Jobot's best clients, and a company that has been growing by over 100% year over year for the last 7 years. They are continuing to grow! This company is focused on offering top tier consulting services to enterprise companies that are trying to better utilize their data. Why join us? Join us for the variety of work, the opportunity to interface with some of the top companies in the world, and ability to build creative solutions to challenging problems. Job Details Must be a talented data engineer! Ideally you come from some soft of consulting or client facing background, this may include internal customers! Hands on engineering experience a must. This includes the following: 1. Snowflake or Databricks engineering 2. Deep understanding of AWS or Azure or GCP 3. Code bases written in Python, Scala and or Java 4. Most important? Clear and concise communication skills, you must be able to sit in front of a client, and be engaging, and speak with non-technical stakeholders. This company will not be able to sponsor or transfer visas. If interested, please apply, or feel free to message directly. 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 AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration)

+3

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 EngineerMcLean, VA: $197,300 - $225,100 for Lead AI EngineerNew York, NY: $215,200 - $245,600 for Lead AI EngineerSan Francisco, CA: $215,200 - $245,600 for Lead AI EngineerSan 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).

Manager, Data Scientist - Emerging Payments & Airkey

Manager, Data Scientist - Emerging Payments & Airkey Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

The Emerging Payments organization develops and maintains innovative payment experiences for Capital One customers, including digital wallets, virtual card numbers, merchant checkout experiences, transaction intelligence, and new commercialization opportunities.

Our data science team builds machine learning models that help our customers securely facilitate, control, and understand their spend. These models power customer-facing features and experiences that reach tens of millions of customers.

We cleanse, enrich, and use large scale card and debit data from Capital One and, more recently, Discover, as well as national metadata datasets around merchants, places, and more. Leveraging the latest approaches and tools, we primarily work with models such as XGBoost, transformers, embeddings, and LLMs, using SQL, Python (and some Scala), tensorflow and pytorch, with Databricks, Snowflake, and other internal platforms and tools.

On any given day you’ll be:

Creating machine learning models from development through testing and validation to our 30+ million customers in production
Designing rich data visualizations to communicate complex ideas to customers or company leaders
Investigating the impact of new technologies on the future of mobile banking and the financial world of tomorrow

In this role, you will:

Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product that customers love
Leverage a broad stack of technologies - SQL, Python, Conda, AWS, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Flex your interpersonal skills to translate the complexity of your work into tangible business goals

The Ideal Candidate is:

Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.

Basic Qualifications:

Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
- A Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics
- A Master’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics
- A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics
At least 1 year of experience leveraging open source programming languages for large scale data analysis
At least 1 year of experience working with machine learning
At least 1 year of experience utilizing relational databases

Preferred Qualifications:

PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data science. Bonus points for experience with transformers
At least 4 years of experience in Python, Scala for large scale data analysis
At least 4 years of experience with machine learning
At least 4 years of experience with SQL
At least 1 year of experience working with AWS

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 Mgr, Data Science

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).

Manager, Data Scientist - Model Risk Office

Manager, Data Scientist - Model Risk Office Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

The Capital One Model Risk Office is dedicated to safeguarding the company from model failures while simultaneously enhancing decision-making through models, including unique risks associated with Generative AI (GenAI). Leveraging expertise in statistics, software engineering, and business, we strive to achieve optimal results for both Risk Management and the broader Enterprise. We prioritize long-term success by continually investing in future capabilities: acquiring new skills, developing superior tools, and cultivating strong relationships with trusted partners. Our approach involves learning from past errors to develop increasingly robust techniques that prevent recurrence.

Role Description

In this role, you will:

Partner with a cross-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models
Leverage a broad stack of technologies - from foundational frameworks (PyTorch, Hugging Face), to orchestration tools (LangChain, Vector Databases) to LLMOps, observability platforms, and more - to reveal the insights hidden within huge volumes of multi-modal data
Build machine learning models to challenge “champion models” that are deployed in production today and contribute to the model governance framework for the next generation of models
Validate a wide variety of models across multiple business domains within our Enterprise Services division, and flex your interpersonal skills to present how identified model risks could impact the business to executives.

The Ideal Candidate is:

Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

Basic Qualifications:

Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
- A Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics
- A Master’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics
- A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics
At least 1 year of experience leveraging open source programming languages for large scale data analysis
At least 1 year of experience working with machine learning
At least 1 year of experience utilizing relational or vector databases

Preferred Qualifications:

PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics
At least 1 year of experience working with AWS
At least 4 years’ experience in Python, Scala, or R for large scale data analysis
At least 4 years’ experience with machine learning, including GenAI
At least 4 years’ experience building or validating models related to fraud detection, digital marketing, cybersecurity, or sensitive data detection.

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.

Chicago, IL: $179,400 - $204,700 for Mgr, Data Science
McLean, VA: $197,300 - $225,100 for Mgr, Data Science
Richmond, VA: $179,400 - $204,700 for Mgr, Data Science

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 (AI Foundations)

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.

Sales Territory: $179,400 - $204,700 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
Cambridge, MA: $197,300 - $225,100 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).

Sr. Lead, Machine Learning Engineer (Enterprise Platforms Technology)

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.

Enterprise Platforms Technology (EPTech) comprises many of Capital One’s most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices.

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