OPT Research Jobs
Research roles are among the strongest fits for F-1 OPT students, with positions at universities, federal agencies, and private labs routinely sponsoring H-1B visas. Your 12-month OPT window, or 24-month STEM extension if your degree qualifies, gives you real runway to build a research career in the U.S.
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Get Access To All JobsINTRODUCTION
At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. 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 building world-class applied science and engineering teams and continue 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 AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business.
WHAT YOU’LL DO:
- Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money.
- Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
- Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.
- Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.
- Flex your interpersonal skills to translate the complexity of your work into tangible business goals.
- Collaborate with senior researchers to prepare internal tech reports or conference submissions summarizing novel methods or findings.
THE IDEAL CANDIDATE:
- 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.
- 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.
- A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
- Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
- Has a deep understanding of the foundations of AI methodologies.
- Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF.
- An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes.
- Experience in delivering libraries, platform level code or solution level code to existing products.
- A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.
- Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.
BASIC QUALIFICATIONS:
- Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research.
PREFERRED QUALIFICATIONS:
- PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields.
- LLM
- PhD focus on NLP or Masters with 5 years of industrial NLP research experience.
- Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization).
- Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens).
- Publications in deep learning theory.
- Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR.
- Optimization (Training & Inference)
- PhD focused on topics related to optimizing training of very large deep learning models.
- Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression.
- Experience optimizing training for a 10B+ model.
- Deep knowledge of deep learning algorithmic and/or optimizer design.
- Experience with compiler design.
- Finetuning
- PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning).
- Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance.
- Experience deploying a fine-tuned large language model.
- Data Preparation
- Publications studying tokenization, data quality, dataset curation, or labeling.
- Contribution to a major open source corpus.
- Contribution to open source libraries for data quality, dataset curation, or labeling.
- Demonstrated ability to reproduce and extend peer-reviewed AI research using modern open-source frameworks.
- Experience designing controlled experiments and documenting reproducibility results for internal or public research.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
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: $218,700 - $249,600 for Applied Researcher 4
McLean, VA: $218,700 - $249,600 for Applied Researcher 4
New York, NY: $238,600 - $272,300 for Applied Researcher 4
San Francisco, CA: $238,600 - $272,300 for Applied Researcher 4
San Jose, CA: $238,600 - $272,300 for Applied Researcher 4
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 trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. 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 building world-class applied science and engineering teams and continue 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 AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business.
WHAT YOU’LL DO:
- Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money.
- Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
- Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.
- Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.
- Flex your interpersonal skills to translate the complexity of your work into tangible business goals.
- Collaborate with senior researchers to prepare internal tech reports or conference submissions summarizing novel methods or findings.
THE IDEAL CANDIDATE:
- 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.
- 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.
- A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
- Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
- Has a deep understanding of the foundations of AI methodologies.
- Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF.
- An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes.
- Experience in delivering libraries, platform level code or solution level code to existing products.
- A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.
- Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.
BASIC QUALIFICATIONS:
- Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research.
PREFERRED QUALIFICATIONS:
- PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields.
- LLM
- PhD focus on NLP or Masters with 5 years of industrial NLP research experience.
- Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization).
- Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens).
- Publications in deep learning theory.
- Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR.
- Optimization (Training & Inference)
- PhD focused on topics related to optimizing training of very large deep learning models.
- Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression.
- Experience optimizing training for a 10B+ model.
- Deep knowledge of deep learning algorithmic and/or optimizer design.
- Experience with compiler design.
- Finetuning
- PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning).
- Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance.
- Experience deploying a fine-tuned large language model.
- Data Preparation
- Publications studying tokenization, data quality, dataset curation, or labeling.
- Contribution to a major open source corpus.
- Contribution to open source libraries for data quality, dataset curation, or labeling.
- Demonstrated ability to reproduce and extend peer-reviewed AI research using modern open-source frameworks.
- Experience designing controlled experiments and documenting reproducibility results for internal or public research.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
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: $218,700 - $249,600 for Applied Researcher 4
McLean, VA: $218,700 - $249,600 for Applied Researcher 4
New York, NY: $238,600 - $272,300 for Applied Researcher 4
San Francisco, CA: $238,600 - $272,300 for Applied Researcher 4
San Jose, CA: $238,600 - $272,300 for Applied Researcher 4
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).
See all 11,291+ OPT Research Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new OPT Research Jobs.
Get Access To All JobsTips for Finding OPT Sponsorship in Research
Target institutions with established OPT hiring history
Universities, national laboratories, and federally funded research centers hire OPT students consistently. These employers understand authorization requirements and often have dedicated HR processes for international researchers, reducing friction during the hiring process.
Confirm your research role qualifies for STEM OPT extension
If your degree is in a STEM field, verify your CIP code against the official STEM Designated Degree Program list. A qualifying research position filed before your OPT expires extends your authorization by 24 months, significantly improving your sponsorship prospects.
Surface your publications, datasets, and conference presentations
Research hiring managers evaluate output directly. List peer-reviewed publications, preprints, conference papers, and open-source datasets prominently on your CV. Concrete research artifacts demonstrate productivity in ways that a job title alone cannot convey.
Ask about H-1B sponsorship policy during the offer stage, not after
Research roles at private companies vary widely on sponsorship. Raise the question before accepting an offer, not months into employment. Asking early signals professionalism and prevents wasted time if the employer does not sponsor international researchers.
Identify your faculty advisor or PI as a professional reference
A strong letter or verbal recommendation from a principal investigator carries significant weight in research hiring. PIs often have direct connections to industry research teams and can advocate for candidates in ways a generic reference cannot.
Use Migrate Mate to find research positions with OPT sponsorship
Not all job boards filter for visa sponsorship. Migrate Mate is built specifically for F-1 OPT students, so every research listing you see is relevant to your work authorization situation, saving time you would otherwise spend filtering out ineligible roles.
Research OPT: Frequently Asked Questions
Can I work in a research role on F-1 OPT?
Yes. Research positions are fully eligible for F-1 OPT work authorization, provided the role is directly related to your field of study. This includes positions at universities, private research firms, government contractors, and national laboratories. You must work at least 20 hours per week to maintain valid OPT status.
Do research jobs qualify for the 24-month STEM OPT extension?
They can, but two conditions must be met. First, your degree must be in a field on the STEM Designated Degree Program list. Second, your employer must be enrolled in E-Verify. Most major research institutions and federal contractors already meet this requirement. File Form I-765 before your initial OPT expires to preserve your authorization.
Are research positions at universities more likely to sponsor H-1B visas?
Universities and academic medical centers tend to have more flexible sponsorship policies than many private employers, partly because they are exempt from the H-1B cap when hiring for qualifying research or teaching roles. This cap-exempt status means you can be sponsored year-round without waiting for the annual lottery, which is a significant advantage for researchers.
What counts as a research role that qualifies under OPT?
USCIS requires a direct connection between your job duties and your degree field. A biology graduate working as a lab researcher clearly qualifies. A computer science graduate doing machine learning research at a tech company also qualifies. The key is documenting the connection in your records. Vague job titles are fine as long as the actual duties align with your coursework.
Where can I find research jobs that are open to OPT students?
Migrate Mate is the recommended starting point. It is designed specifically for F-1 OPT and STEM OPT students, so the research roles listed there are already filtered for visa sponsorship compatibility. This is more efficient than general job boards where OPT eligibility is unclear and you must vet each employer individually.