OPT Research Intern Jobs
Research Intern roles are among the most OPT-friendly positions available, with STEM OPT extensions applying broadly across science, engineering, and social research fields. Most positions run 10 to 40 hours per week, and many universities actively hire their own F-1 students, making on-campus placement straightforward during your OPT period.
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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 572+ OPT Research Intern Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new OPT Research Intern Jobs.
Get Access To All JobsTips for Finding OPT Sponsorship as a Research Intern
Confirm STEM OPT eligibility before applying
Research intern roles in biology, chemistry, computer science, and engineering typically qualify for the 24-month STEM OPT extension. Verify your degree is on the STEM Designated Degree Program List before targeting roles in those fields.
Target university and national lab employers first
Academic institutions and federal research labs like NIH and national universities frequently hire OPT students and have established processes for work authorization. These employers rarely treat OPT as a barrier compared to private-sector hiring managers.
Clarify your OPT authorization window upfront
Research internships often run 3 to 12 months. If your OPT card covers the full duration, state that clearly in your first message to the recruiter. Removing ambiguity early keeps your application moving forward.
Align your research focus to your degree field
OPT requires work directly related to your degree. A chemistry graduate working in a biology lab is generally fine. A computer science graduate doing unrelated administrative research is not. Confirm the connection is defensible before accepting an offer.
Ask about CPT history when discussing timelines
If you used 12 or more months of full-time CPT, you are ineligible for OPT. Some research internships recruit students mid-program. Being upfront about your CPT history avoids complications after an offer is extended.
Get the job offer in writing before requesting a DSO update
Your Designated School Official needs a written offer letter to update your SEVIS record for post-completion OPT. Secure the written offer, confirm the start date, and then initiate the DSO process with enough lead time before your program end date.
Research Intern OPT: Frequently Asked Questions
Can I work as a research intern on OPT without H-1B sponsorship?
Yes. OPT is your own work authorization, not employer sponsorship. You can work as a research intern for any employer willing to hire you without them filing any visa petition. Many research institutions, nonprofits, and universities hire OPT students specifically because the process is straightforward for them.
Does a research intern role qualify for the STEM OPT extension?
It depends on your degree field and the nature of the research. If your degree is on the STEM Designated Degree Program List and the internship involves work directly tied to that field, such as laboratory research, data analysis, or computational modeling, the role generally qualifies. Your DSO and the employer must confirm the connection meets USCIS standards.
How do I find research intern roles that are open to OPT students?
Migrate Mate is built specifically for F-1 OPT students and filters job listings by sponsorship and work authorization status. Searching there lets you focus on employers already familiar with OPT rather than spending time on applications where authorization is an immediate disqualifier.
Can I work part-time as a research intern on OPT?
Yes, but with an important limit. During post-completion OPT, you must work at least 20 hours per week to remain in valid status. Part-time research roles that meet or exceed that threshold are fully acceptable. Roles under 20 hours per week do not satisfy the OPT employment requirement and can put your status at risk.
What happens if my research internship ends before my OPT expires?
You have a cumulative 90-day unemployment allowance during standard OPT, which extends to 150 days if you have an approved STEM OPT extension. If your internship ends early, that unemployment clock starts. You can take on a second research role or a different qualifying job during that window without violating your status.