AI Product Engineer Visa Sponsorship Jobs in Virginia
Virginia is a major hub for AI product engineers, with demand concentrated in Northern Virginia's technology corridor, home to Amazon Web Services, Booz Allen Hamilton, Leidos, and SAIC. The region's dense federal contracting ecosystem and expanding commercial tech sector make it one of the most active states for AI product engineer visa sponsorship.
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INTRODUCTION
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 Consumer Engagement Platform organization at Capital One empowers rapid financial product innovation at scale and delivers developer joy, for all Capital One’s consumer products and organizations, by providing well-managed, self-service, experimentation-driven, and personalized product development vehicles. Hyper Personalization org is building the intelligence and infrastructure that will enable Capital One to deliver truly individualized, real-time customer experiences at scale — turning every channel into a context-aware decisioning surface, from home feeds to marketing and servicing messages. The org’s mission is to move Capital One to deliver always-on, cohort-of-one personalization, powered by resilient data foundations, production-grade ML and GenAI systems, and low-latency application platforms that make it easy for teams across the company to experiment, innovate, and serve the right experience to every customer at the right moment.
ROLE AND RESPONSIBILITIES
- Define and drive technical strategy and roadmap for our Personalization Platform that powers real-time, personalized product experiences and multi-channel targeted user messaging across all Capital One products and services.
- Partner cross-functionally with Product, Data science, Cloud infrastructure, and Machine learning platform teams to align on and co-develop the advanced recommendation systems and algorithms serving our Capital One users.
- Develop and maintain a flexible, scalable rules engine to enable business-driven personalization logic, allowing dynamic configuration of user segmentation, targeting rules, and real-time decisioning while integrating seamlessly with ML-driven recommendations.
- Design, build and maintain robust ML infrastructure and pipelines to support end-to-end workflows including feature extraction, model training, testing, guardrails, model evaluation, deployment, and both real-time and batch inference - ensuring high performance, scalability, and reliability.
- Architect low-latency, event-driven systems for enabling real-time dynamic personalization and decisioning based on streaming data, user behavior, and contextual signals.
- Drive the evolution of MLOps practices by building automated metrics-backed deployment workflows, integration validation and testing systems, and scalable monitoring & observability.
- Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
- Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
- Provide organizational technical leadership to influence architecture, engineering standards, cross-team strategies, mentoring engineers and driving organization wide platform innovation.
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.
Capital One is open to hiring a Remote Employee for this opportunity.
BASIC QUALIFICATIONS
- Bachelor’s degree
- At least 10 years of experience designing and building data-intensive solutions using distributed computing
- At least 7 years of experience programming in C, C++, Python, or Scala
- At least 4 years of experience with the full ML development lifecycle using modern technology in a business critical setting
PREFERRED QUALIFICATIONS
- 8+ years of experience deploying scalable, responsible AI solutions on major cloud platforms (AWS, GCP, Azure); Master's or PhD in Computer Science or a relevant technical field.
- 5+ years of proven expertise in designing, implementing and scaling personalization platform and recommendation systems serving one or more areas of Feed Personalization/Ads Ranking/Targeted Marketing Messaging.
- 5+ years of strong proficiency in Python, Java, C++, or Golang; hands-on experience with ML frameworks (PyTorch, TensorFlow) and orchestration tools (Databricks, Airflow, Kubeflow).
- 5+ years of experience developing and applying state-of-the-art techniques for optimizing training and inference systems to improve hardware utilization, latency, throughput, and cost.
- 5+ years of deep expertise in cloud-native engineering, containerization (Docker, Kubernetes), and automated CI/CD deployment.
- 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.
- Proven leadership in driving platform strategy, fostering cross-functional collaboration, and influencing technical direction across the company.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
COMPENSATION
-
Remote (Regardless of Location): $286,200 - $326,700 for Sr Distinguished Machine Learning Engineer
-
McLean, VA: $314,800 - $359,300 for Sr Distinguished 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 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. 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 Careers@capitalone.com.
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).

INTRODUCTION
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 Consumer Engagement Platform organization at Capital One empowers rapid financial product innovation at scale and delivers developer joy, for all Capital One’s consumer products and organizations, by providing well-managed, self-service, experimentation-driven, and personalized product development vehicles. Hyper Personalization org is building the intelligence and infrastructure that will enable Capital One to deliver truly individualized, real-time customer experiences at scale — turning every channel into a context-aware decisioning surface, from home feeds to marketing and servicing messages. The org’s mission is to move Capital One to deliver always-on, cohort-of-one personalization, powered by resilient data foundations, production-grade ML and GenAI systems, and low-latency application platforms that make it easy for teams across the company to experiment, innovate, and serve the right experience to every customer at the right moment.
ROLE AND RESPONSIBILITIES
- Define and drive technical strategy and roadmap for our Personalization Platform that powers real-time, personalized product experiences and multi-channel targeted user messaging across all Capital One products and services.
- Partner cross-functionally with Product, Data science, Cloud infrastructure, and Machine learning platform teams to align on and co-develop the advanced recommendation systems and algorithms serving our Capital One users.
- Develop and maintain a flexible, scalable rules engine to enable business-driven personalization logic, allowing dynamic configuration of user segmentation, targeting rules, and real-time decisioning while integrating seamlessly with ML-driven recommendations.
- Design, build and maintain robust ML infrastructure and pipelines to support end-to-end workflows including feature extraction, model training, testing, guardrails, model evaluation, deployment, and both real-time and batch inference - ensuring high performance, scalability, and reliability.
- Architect low-latency, event-driven systems for enabling real-time dynamic personalization and decisioning based on streaming data, user behavior, and contextual signals.
- Drive the evolution of MLOps practices by building automated metrics-backed deployment workflows, integration validation and testing systems, and scalable monitoring & observability.
- Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
- Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
- Provide organizational technical leadership to influence architecture, engineering standards, cross-team strategies, mentoring engineers and driving organization wide platform innovation.
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.
Capital One is open to hiring a Remote Employee for this opportunity.
BASIC QUALIFICATIONS
- Bachelor’s degree
- At least 10 years of experience designing and building data-intensive solutions using distributed computing
- At least 7 years of experience programming in C, C++, Python, or Scala
- At least 4 years of experience with the full ML development lifecycle using modern technology in a business critical setting
PREFERRED QUALIFICATIONS
- 8+ years of experience deploying scalable, responsible AI solutions on major cloud platforms (AWS, GCP, Azure); Master's or PhD in Computer Science or a relevant technical field.
- 5+ years of proven expertise in designing, implementing and scaling personalization platform and recommendation systems serving one or more areas of Feed Personalization/Ads Ranking/Targeted Marketing Messaging.
- 5+ years of strong proficiency in Python, Java, C++, or Golang; hands-on experience with ML frameworks (PyTorch, TensorFlow) and orchestration tools (Databricks, Airflow, Kubeflow).
- 5+ years of experience developing and applying state-of-the-art techniques for optimizing training and inference systems to improve hardware utilization, latency, throughput, and cost.
- 5+ years of deep expertise in cloud-native engineering, containerization (Docker, Kubernetes), and automated CI/CD deployment.
- 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.
- Proven leadership in driving platform strategy, fostering cross-functional collaboration, and influencing technical direction across the company.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
COMPENSATION
-
Remote (Regardless of Location): $286,200 - $326,700 for Sr Distinguished Machine Learning Engineer
-
McLean, VA: $314,800 - $359,300 for Sr Distinguished 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 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. 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 Careers@capitalone.com.
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).
AI Product Engineer Job Roles in Virginia
See all 43+ AI Product Engineer Jobs in Virginia
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Search AI Product Engineer Jobs in VirginiaAI Product Engineer Jobs in Virginia: Frequently Asked Questions
Which companies sponsor visas for AI product engineers in Virginia?
Northern Virginia's federal contracting sector drives significant sponsorship activity for AI product engineers. Companies like Booz Allen Hamilton, Leidos, SAIC, General Dynamics IT, and Amazon Web Services have documented H-1B sponsorship histories for AI and machine learning roles. Commercial tech firms and government contractors in the Tysons, Reston, and Arlington areas are among the most active sponsors for this role type.
Which visa types are most common for AI product engineer roles in Virginia?
The H-1B is the most common visa for AI product engineers in Virginia, as the role typically qualifies as a specialty occupation requiring a bachelor's degree or higher in computer science, artificial intelligence, or a related field. Some candidates enter through OPT before transitioning to H-1B sponsorship. L-1B visas also appear for intracompany transfers in multinational tech and consulting firms operating in the state.
Which cities in Virginia have the most AI product engineer sponsorship jobs?
Northern Virginia dominates AI product engineer hiring, particularly in Reston, Tysons, McLean, Arlington, and Herndon. This corridor hosts the highest concentration of federal contractors, cloud infrastructure providers, and defense-adjacent tech companies in the state. Richmond is a secondary market with growing fintech and enterprise software presence, but the volume of sponsorship-eligible AI product engineering roles there is considerably lower.
How to find ai product engineer visa sponsorship jobs in Virginia?
Migrate Mate filters job listings specifically for visa sponsorship eligibility, making it a practical starting point for AI product engineer roles in Virginia. You can search by state and role type to surface positions from federal contractors, cloud providers, and commercial tech firms in the Northern Virginia corridor. Focusing your search on employers with established H-1B filing histories in AI and machine learning disciplines improves your chances of finding genuine sponsorship opportunities.
Are there any Virginia-specific considerations for AI product engineers seeking sponsorship?
Virginia's large federal contracting sector introduces a consideration not common in other states: many roles require security clearances, which are generally not accessible to non-citizens on work visas. This limits the pool of sponsorship-eligible AI product engineering positions to commercial projects or unclassified government work. Candidates should focus on roles explicitly open to visa holders, as clearance requirements can disqualify a significant share of otherwise relevant listings in the region.
What is the prevailing wage for sponsored ai product engineer jobs in Virginia?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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