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Data Scientist

Vantor

Reston, Virginia

In office

Mid - Senior

$113,000/hour - $188,000/hour

RECENTLY POSTED

+3

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next. Vantor is a place for problem solvers, changemakers, and go-getters—where people are working together to help our customers see the world differently, and in doing so, be seen differently. Come be part of a mission, not just a job, where you can: Shape your own future, build the next big thing, and change the world.

To be eligible for this position, you must be a U.S. Citizen. This position requires an active U.S. Government security clearance, applicants who do not currently hold the required clearance will not be eligible for consideration. Employment for cleared roles is contingent upon verification of clearance status.

Export Control/ITAR: Certain roles may be subject to U.S. export control laws, requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3).

Please review the job details below.

This position requires an active U.S. Government Security Clearance at the TS/SCI level with CI Polygraph.

This project supports a hard and deeply buried target mission set, providing critical analytic insights to government stakeholders. Success depends on the development of accurate, scalable, and mission-tailored data solutions that enable timely and informed decision-making. The work directly impacts national security objectives by transforming complex data into actionable intelligence in a highly specialized and sensitive domain.

Responsibilities:

Automate and maintain data extraction, cleaning, processing, and analysis workflows using Python, SQL, and ETL tools under established best practices.
Process and analyze structured and unstructured datasets using big data or cloud-native frameworks (e.g., Spark, Hadoop, or managed cloud services).
Develop, test, and evaluate predictive models and statistical analyses to support mission-focused use cases.
Contribute to end-to-end data science and data engineering workflows, from data preparation and feature engineering through model development and results delivery, with guidance from senior team members as needed.
Write clear, well-structured documentation of methods, assumptions, and results; assist with briefings or presentations to technical and non-technical stakeholders.
Support the use of Large Language Models (LLMs) within existing systems and workflows, including:
Implementing LLM-based solutions for summarization, tagging, classification, and information retrieval.
Integrating pre-trained LLMs into pipelines to improve knowledge discovery and data accessibility.
Assisting with deployment and evaluation of internal LLM-enabled tools or assistants.
Collaborate closely with data scientists, engineers, analysts, and mission partners to refine requirements and iterate on solutions.

Minimum Qualifications:

Current/active TS/SCI security clearance and be willing and able to obtain CI polygraph.
5 years of professional experience in data science, analytics, or data engineering roles.
Bachelor’s degree in data science, computer science, engineering, statistics, GIS, or related discipline. Degree may be substituted with an additional 2 yrs of experience.
Strong coding proficiency in Python and SQL, with experience writing production-quality, maintainable code; working knowledge of R is a plus.
Hands-on experience with data manipulation, feature engineering, machine learning libraries (e.g., scikit-learn, PyTorch, TensorFlow), and automation tools.
Experience contributing to full-cycle data projects, including data preparation, modeling, validation, and reporting.
Ability to clearly communicate technical concepts and analytical results in writing and verbally.
Familiarity with NLP and LLM concepts, including practical experience applying pre-trained models (e.g., GPT-style models) for automation, summarization, or search.
Ability to work effectively in a collaborative environment, taking direction and feedback while owning assigned technical tasks.

Preferred Qualifications:

Master’s degree in data science, computer science, statistics, engineering, or a related technical field.
Experience with cloud-based environments (e.g., AWS, Azure, or GCP) and scalable data processing pipelines.
Working knowledge of NLP techniques, embeddings, vector search, or retrieval-augmented generation (RAG).
Experience integrating LLMs into applications or workflows using APIs and open-source tooling.
Exposure to CI/CD, version control, testing frameworks, and software engineering best practices.
Interest in responsible AI principles, model evaluation, and risk-aware deployment of LLM-based solutions.

Pay Transparency: In support of pay transparency at Vantor, we disclose salary ranges on all U.S. job postings. The successful candidate’s starting pay will fall within the salary range provided below and is determined based on job-related factors, including, but not limited to, the experience, qualifications, knowledge, skills, geographic work location, and market conditions. Candidates with the minimum necessary experience, qualifications, knowledge, and skillsets for the position should not expect to receive the upper end of the pay range.

● The base pay for this position within the Washington, DC metropolitan area is: $113,000.00 - $188,000.00 annually.

For all other states, we use geographic cost of labor as an input to develop market-driven ranges for our roles, and as such, each location where we hire may have a different range.

Benefits: Vantor offers a competitive total rewards package that goes beyond the standard, including a robust 401(k) with company match, mental health resources, and unique perks like student loan repayment assistance, adoption reimbursement and pet insurance to support all aspects of your life. You can find more information on our benefits at: careers

The application window is three days from the date the job is posted and will remain posted until a qualified candidate has been identified for hire. If the job is reposted regardless of reason, it will remain posted three days from the date the job is reposted and will remain reposted until a qualified candidate has been identified for hire.

The date of posting can be found on Vantor’s Career page at the top of each job posting.

To apply, submit your application via Vantor’s Career page.

EEO Policy: Vantor is an equal opportunity employer committed to an inclusive workplace. We believe in fostering an environment where all team members feel respected, valued, and encouraged to share their ideas. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability, protected veteran status, age, or any other characteristic protected by law.

Data Scientist (TS/SCI with CI Poly)

$113,000/hour - $188,000/hour

RECENTLY POSTED

+3

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next. Vantor is a place for problem solvers, changemakers, and go-getters—where people are working together to help our customers see the world differently, and in doing so, be seen differently. Come be part of a mission, not just a job, where you can: Shape your own future, build the next big thing, and change the world.

To be eligible for this position, you must be a U.S. Citizen. This position requires an active U.S. Government security clearance, applicants who do not currently hold the required clearance will not be eligible for consideration. Employment for cleared roles is contingent upon verification of clearance status.

Export Control/ITAR: Certain roles may be subject to U.S. export control laws, requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3).

Please review the job details below.

This position requires an active U.S. Government Security Clearance at the TS/SCI level with CI Polygraph.

This project supports a hard and deeply buried target mission set, providing critical analytic insights to government stakeholders. Success depends on the development of accurate, scalable, and mission-tailored data solutions that enable timely and informed decision-making. The work directly impacts national security objectives by transforming complex data into actionable intelligence in a highly specialized and sensitive domain.

Responsibilities:

Automate and maintain data extraction, cleaning, processing, and analysis workflows using Python, SQL, and ETL tools under established best practices.
Process and analyze structured and unstructured datasets using big data or cloud-native frameworks (e.g., Spark, Hadoop, or managed cloud services).
Develop, test, and evaluate predictive models and statistical analyses to support mission-focused use cases.
Contribute to end-to-end data science and data engineering workflows, from data preparation and feature engineering through model development and results delivery, with guidance from senior team members as needed.
Write clear, well-structured documentation of methods, assumptions, and results; assist with briefings or presentations to technical and non-technical stakeholders.
Support the use of Large Language Models (LLMs) within existing systems and workflows, including:
Implementing LLM-based solutions for summarization, tagging, classification, and information retrieval.
Integrating pre-trained LLMs into pipelines to improve knowledge discovery and data accessibility.
Assisting with deployment and evaluation of internal LLM-enabled tools or assistants.
Collaborate closely with data scientists, engineers, analysts, and mission partners to refine requirements and iterate on solutions.

Minimum Qualifications:

Current/active TS/SCI security clearance and be willing and able to obtain CI polygraph.
5 years of professional experience in data science, analytics, or data engineering roles.
Bachelor’s degree in data science, computer science, engineering, statistics, GIS, or related discipline. Degree may be substituted with an additional 2 yrs of experience.
Strong coding proficiency in Python and SQL, with experience writing production-quality, maintainable code; working knowledge of R is a plus.
Hands-on experience with data manipulation, feature engineering, machine learning libraries (e.g., scikit-learn, PyTorch, TensorFlow), and automation tools.
Experience contributing to full-cycle data projects, including data preparation, modeling, validation, and reporting.
Ability to clearly communicate technical concepts and analytical results in writing and verbally.
Familiarity with NLP and LLM concepts, including practical experience applying pre-trained models (e.g., GPT-style models) for automation, summarization, or search.
Ability to work effectively in a collaborative environment, taking direction and feedback while owning assigned technical tasks.

Preferred Qualifications:

Master’s degree in data science, computer science, statistics, engineering, or a related technical field.
Experience with cloud-based environments (e.g., AWS, Azure, or GCP) and scalable data processing pipelines.
Working knowledge of NLP techniques, embeddings, vector search, or retrieval-augmented generation (RAG).
Experience integrating LLMs into applications or workflows using APIs and open-source tooling.
Exposure to CI/CD, version control, testing frameworks, and software engineering best practices.
Interest in responsible AI principles, model evaluation, and risk-aware deployment of LLM-based solutions.

Pay Transparency: In support of pay transparency at Vantor, we disclose salary ranges on all U.S. job postings. The successful candidate’s starting pay will fall within the salary range provided below and is determined based on job-related factors, including, but not limited to, the experience, qualifications, knowledge, skills, geographic work location, and market conditions. Candidates with the minimum necessary experience, qualifications, knowledge, and skillsets for the position should not expect to receive the upper end of the pay range.

● The base pay for this position within the Washington, DC metropolitan area is: $113,000.00 - $188,000.00 annually.

For all other states, we use geographic cost of labor as an input to develop market-driven ranges for our roles, and as such, each location where we hire may have a different range.

Benefits: Vantor offers a competitive total rewards package that goes beyond the standard, including a robust 401(k) with company match, mental health resources, and unique perks like student loan repayment assistance, adoption reimbursement and pet insurance to support all aspects of your life. You can find more information on our benefits at: careers

The application window is three days from the date the job is posted and will remain posted until a qualified candidate has been identified for hire. If the job is reposted regardless of reason, it will remain posted three days from the date the job is reposted and will remain reposted until a qualified candidate has been identified for hire.

The date of posting can be found on Vantor’s Career page at the top of each job posting.

To apply, submit your application via Vantor’s Career page.

EEO Policy: Vantor is an equal opportunity employer committed to an inclusive workplace. We believe in fostering an environment where all team members feel respected, valued, and encouraged to share their ideas. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability, protected veteran status, age, or any other characteristic protected by law.

Lead AI/ML Engineer (Platform, kubeflow)

+3

Lead AI/ML Engineer (Platform, kubeflow) 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.

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).

Senior Machine Learning Engineer

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).

Lead, Systems Engineering (Detection Algorithm Development)

L3Harris Technologies

L3Harris is dedicated to recruiting and developing high-performing talent who are passionate about what they do. Our employees are unified in a shared dedication to our customers’ mission and quest for professional growth. L3Harris provides an inclusive, engaging environment designed to empower employees and promote work-life success. Fundamental to our culture is an unwavering focus on values, dedication to our communities, and commitment to excellence in everything we do.

L3Harris is the Trusted Disruptor in defense tech. With customers’ mission-critical needs always in mind, our employees deliver end-to-end technology solutions connecting the space, air, land, sea and cyber domains in the interest of national security.

Job Title: Lead, Systems Engineering (Detection Algorithm Development)

Job Code: 35288

Job Location: Fort Wayne, IN

Job Schedule: 9/80 (Every other Friday off)

Job Description:

The ideal candidate for this position has extensive knowledge of EO/IR image / video processing techniques that can be implemented in low size, weight, and power (SWaP) space systems. Candidate will provide direct contributions and act as a technical lead for algorithm development, analysis, integration into flight hardware, on-orbit troubleshooting, and future pursuits.

Algorithm performance plays a key role in all stages of program life cycle. Candidate needs to be comfortable working with end customers to understand requirements and capabilities define and run trade studies to meet customer requirements. Candidate will also work closely with other systems engineers to define CONOPs, ICDs, and implementation requirements.

Essential Functions:

Lead/support development of image and video processing algorithm solutions for space based EO/IR systems
Lead/support analysis of image and video processing algorithms in support of system level trade studies, requirement compliance and system characterization. Perform modeling & simulation activities to accurately model Earth observing EO/IR systems in LEO, MEO, and GEO.
Support systems engineering trade studies, CONOP development, and modeling/simulation efforts
Implement custom and OpenCV-based image/video processing algorithms in FPGAs, GPUs, or embedded systems
Perform rapid complex trade studies assessing a variety of algorithms to achieve optimal performance. Comfortable using tools such as NumPy, SciPy, scikit-learn, PyTorch, CV2, CUDA.
Familiar with Overhead Persistent InfraRed (OPIR) imagery and phenomenology
Develop and improve instrument documentation, processes, and test procedures
Support concept of operation development and requirements analysis, decomposition, and generation at various levels of the system
Support requirements traceability and development of test plans to cover requirements
Support integration and test of electro-optical/infrared systems and related hardware/software
Provide support to engineering in developing technical specifications, interface control documents, test plans and procedures, and test conformance to specifications

Qualifications:

Bachelor’s Degree in engineering and minimum 9 years of prior relevant experience. Graduate Degree and a minimum of 7 years of prior related experience. In lieu of a degree, minimum of 13 years of prior related experience.
5+ years experience in Python, C/C++, or VHDL
Professional experience implementing image/video processing algorithms in FPGAs, GPUs, or embedded systems
Active DoD Secret clearance

Preferred Additional Skills:

Strong background in mathematics or physics
Experience developing embedded software / firmware
Ability to read/write C/C++ software
Inter-personal and communication skills, ability to interact with a cross functional team
Ability to collaborate across all levels of leadership
Able to work with general direction or supervision in a demanding environment
Experience with data analysis and/or modeling and simulation (e.g. with MATLAB/Python)
Experience with estimating and managing costs
Experience architecting, analyzing, developing, and integrating end to end systems in areas such as EO/IR, RF, or space payload and spacecraft bus subsystems
Familiarity with program management, cost account management, integrated product teams

#LI-KB1

L3Harris Technologies is proud to be an Equal Opportunity Employer. L3Harris is committed to treating all employees and applicants for employment with respect and dignity and maintaining a workplace that is free from unlawful discrimination. All applicants will be considered for employment without regard to race, color, religion, age, national origin, ancestry, ethnicity, gender (including pregnancy, childbirth, breastfeeding or other related medical conditions), gender identity, gender expression, sexual orientation, marital status, veteran status, disability, genetic information, citizenship status, characteristic or membership in any other group protected by federal, state or local laws. L3Harris maintains a drug-free workplace and performs pre-employment substance abuse testing and background checks, where permitted by law.

Please be aware many of our positions require the ability to obtain a security clearance. Security clearances may only be granted to U.S. citizens. In addition, applicants who accept a conditional offer of employment may be subject to government security investigation(s) and must meet eligibility requirements for access to classified information.

By submitting your resume for this position, you understand and agree that L3Harris Technologies may share your resume, as well as any other related personal information or documentation you provide, with its subsidiaries and affiliated companies for the purpose of considering you for other available positions.

L3Harris Technologies is an E-Verify Employer. Please click here for the E-Verify Poster in English or Spanish. For information regarding your Right To Work, please click here for English or Spanish.

Lead Machine Learning Engineer

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