Machine Learning Engineer Visa Sponsorship Jobs in Virginia
Virginia is one of the strongest states for machine learning engineer visa sponsorship, driven by a dense concentration of federal contractors, defense tech firms, and cloud infrastructure companies in the Northern Virginia corridor. Major employers including Booz Allen Hamilton, Leidos, Amazon Web Services, and Capital One actively hire and sponsor ML engineers across McLean, Arlington, Reston, and Tysons.
Find Machine Learning Engineer JobsOverview
Showing 5 of 88+ Machine Learning Engineer Jobs in Virginia with Visa Sponsorship
See all 88+ Machine Learning Engineer Jobs in Virginia with Visa Sponsorship
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Engineer Jobs in Virginia with Visa Sponsorship.
Get Access To All JobsINTRODUCTION
Lead Machine Learning Engineer (Python, GoLang, AWS)
As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.
ROLE AND RESPONSIBILITIES
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
COMPENSATION
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
- Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer
- McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer
- New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer
- San Francisco, CA: $215,200 - $245,600 for Lead Machine Learning Engineer
- San Jose, CA: $215,200 - $245,600 for Lead Machine Learning Engineer
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please.
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 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
Lead Machine Learning Engineer (Python, GoLang, AWS)
As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.
ROLE AND RESPONSIBILITIES
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
COMPENSATION
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
- Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer
- McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer
- New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer
- San Francisco, CA: $215,200 - $245,600 for Lead Machine Learning Engineer
- San Jose, CA: $215,200 - $245,600 for Lead Machine Learning Engineer
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please.
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 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).
Machine Learning Engineer Job Roles in Virginia
See all 88+ Machine Learning Engineer Jobs in Virginia
Sign up for free to filter by visa type, set job alerts, and find employers with verified sponsorship history.
Search Machine Learning Engineer Jobs in VirginiaMachine Learning Engineer Jobs in Virginia: Frequently Asked Questions
Which companies sponsor visas for machine learning engineers in Virginia?
Northern Virginia is home to some of the most active sponsors for machine learning engineers in the country. Amazon Web Services, Capital One, Booz Allen Hamilton, Leidos, General Dynamics, and Freddie Mac have all filed H-1B visa Labor Condition Applications for ML engineer roles in Virginia. The federal contracting sector is particularly active, with many firms sponsoring engineers working on defense, intelligence, and cloud infrastructure projects.
Which visa types are most common for machine learning engineer roles in Virginia?
The H-1B is the most common visa for machine learning engineers in Virginia, as ML roles consistently qualify as specialty occupations requiring at least a bachelor's degree in computer science, statistics, or a related field. Some engineers, particularly those from Canada or Mexico, enter on TN visas under the computer systems analyst category. Candidates with extraordinary ability may pursue the O-1A, and those already in the U.S. on OPT or STEM OPT extension often seek H-1B sponsorship from Virginia employers.
Which cities in Virginia have the most machine learning engineer sponsorship jobs?
Northern Virginia dominates, with McLean, Reston, Arlington, and Tysons accounting for the large majority of ML engineering sponsorship activity in the state. This corridor benefits from proximity to federal agencies, major cloud regions, and a dense network of tech and defense contractors. Richmond has a smaller but growing presence, driven by Capital One's headquarters and expanding fintech activity. Remote-friendly roles based in Virginia also appear frequently given the state's strong broadband infrastructure.
How to find machine learning engineer visa sponsorship jobs in Virginia?
Migrate Mate filters job listings specifically by visa sponsorship availability, so you can search machine learning engineer roles in Virginia without sorting through positions that don't offer sponsorship. The platform surfaces openings from federal contractors, cloud companies, and financial services firms that are known H-1B sponsors in the state. Filtering by Virginia on Migrate Mate will show you active roles in Northern Virginia's tech corridor as well as Richmond-area opportunities.
Are there any Virginia-specific considerations for machine learning engineers seeking visa sponsorship?
Virginia's large federal contracting sector introduces a consideration specific to this state: many ML engineer roles require a U.S. security clearance, which is generally not accessible to non-U.S. citizens and permanent residents. This rules out a segment of Northern Virginia job postings for visa-sponsored candidates. However, commercial employers, financial services firms like Capital One and Freddie Mac, and non-clearance contractor roles remain fully accessible. Virginia also has a strong university pipeline through George Mason University and Virginia Tech, which feeds local STEM OPT talent into sponsoring employers.
What is the prevailing wage for sponsored machine learning 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.