Fintech OPT Jobs in New York
New York is one of the top states for fintech F-1 OPT sponsorship jobs, with major employers like JPMorgan Chase, Goldman Sachs, Stripe, and Bloomberg concentrated in Manhattan's Financial District and Midtown. OPT-eligible roles span software engineering, data science, quantitative analysis, and product management, with New York's density of banks, payment companies, and fintech startups creating consistent demand.
Find Fintech JobsOverview
Showing 5 of 46+ Fintech OPT Jobs in New York
See all 46+ Fintech OPT Jobs in New York
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Fintech OPT Jobs in New York.
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.
In this role, you will:
- 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, VectorDBs, 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.
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 new 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, 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 plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 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
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: $262,500 - $299,600 for Applied Researcher II
McLean, VA: $262,500 - $299,600 for Applied Researcher II
New York, NY: $286,400 - $326,800 for Applied Researcher II
San Jose, CA: $286,400 - $326,800 for Applied Researcher II
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.
In this role, you will:
- 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, VectorDBs, 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.
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 new 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, 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 plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 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
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: $262,500 - $299,600 for Applied Researcher II
McLean, VA: $262,500 - $299,600 for Applied Researcher II
New York, NY: $286,400 - $326,800 for Applied Researcher II
San Jose, CA: $286,400 - $326,800 for Applied Researcher II
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).
OPT Fintech Job Roles in New York
See all 46+ Fintech OPT Jobs in New York
Sign up for free to filter by visa type, set job alerts, and find employers with verified sponsorship history.
Search Fintech Jobs in New YorkFintech OPT Sponsorship Jobs in New York: Frequently Asked Questions
Which fintech companies sponsor F-1 OPT visas in New York?
Large financial institutions with dedicated fintech divisions, including JPMorgan Chase, Goldman Sachs, Citigroup, and Bloomberg, are among the most active F-1 OPT sponsors in New York. Fintech-native companies such as Stripe, Plaid, Brex, and Marqeta also maintain New York offices and have hired OPT workers in technical and analytical roles. Sponsorship patterns vary by role, team, and hiring cycle, so confirming directly with each employer's recruiting team is important.
Which cities in New York have the most fintech F-1 OPT sponsorship jobs?
Manhattan is by far the primary hub, particularly the Financial District, Midtown, and Hudson Yards, where the highest concentration of banks, trading firms, and fintech startups are based. Brooklyn's tech corridor around DUMBO and Downtown Brooklyn has a growing number of fintech employers as well. Outside New York City, Buffalo and Rochester have smaller but active fintech sectors tied to regional banking and insurance technology.
What types of fintech roles typically qualify for F-1 OPT sponsorship?
Roles that align with STEM-designated fields are the most common OPT matches in fintech. Software engineering, data science, machine learning engineering, quantitative analysis, financial engineering, and cybersecurity positions regularly appear as OPT-eligible. Product management and UX research roles can also qualify depending on the degree field. New York fintech employers hiring for these functions through OPT often indicate STEM OPT eligibility in job postings, though verification with your Designated School Official is always recommended.
How do I find fintech F-1 OPT sponsorship jobs in New York?
Migrate Mate is built specifically for international students and visa holders searching for sponsorship-confirmed jobs, including fintech F-1 OPT positions in New York. You can filter by visa type, industry, and location to surface roles where employers have a documented history of sponsoring OPT workers. This is more targeted than general job searches, which rarely surface sponsorship status upfront. Migrate Mate also aggregates fintech roles across New York's major financial and tech hubs in one place.
Are there any New York-specific considerations for fintech F-1 OPT sponsorship?
New York's fintech sector is heavily regulated at both the state and federal level, which affects hiring timelines. Roles at broker-dealers, investment advisers, and licensed money transmitters may require FINRA licensing or background checks that can extend onboarding, so it's worth clarifying these requirements before accepting an offer. New York State's Department of Financial Services also imposes compliance requirements on employers that can influence how quickly they can bring on OPT workers in certain regulated roles.