TN Visa Machine Learning Research Jobs
Machine Learning Research roles qualify for TN visa sponsorship under the USMCA's Computer Systems Analyst and Mathematician categories, depending on how the position is defined. Canadian professionals enter without a cap or lottery. Mexican nationals apply through a U.S. consulate. A relevant bachelor's degree and a U.S. employer's job offer letter are required.
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Get Access To All JobsAbout Arc Institute
Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.
Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.
Our two Institute Initiatives reflect this model in action:
- Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets, accelerating the path from biological insight to clinical trials.
- Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.
More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.
About the position
The Hsu Lab is looking for postdoctoral researchers, who are curious, creative and motivated to advance the state-of-the-art in generative AI applied to biology, including Arc’s frontier biological foundation models (Evo, Evo 2, State, Stack, Bioreason, and beyond). The successful candidate is passionate about developing ML models for biological understanding and design, leveraging frontier approaches such as novel ML architectures, post-training, agentic reasoning, and more. Current areas of interest of the lab include building predictive models of life (e.g. by integrating Evo and State), AI agents and systems, genome mining, and invention of new therapeutics through AI-guided approaches.
Postdocs in the lab are encouraged to lead ambitious, independent projects, resulting in high-impact publications. You will have the opportunity to collaborate widely across Arc, Stanford, and the broader Bay Area ecosystem, with access to strong platforms in our lab and our institutions for genomics, single-cell technologies, synthetic biology, high-performance computing clusters, and experimental model systems.
About you
- Extremely Curious & Self-Motivated: You push the boundaries of machine learning, biotechnology, and/or biomedical research.
- High-Velocity Researcher: You thrive in a fast-paced environment and have a bias for action, conducting rigorous and impactful research at scale.
- Intellectually Independent: You are a "first-principles" thinker, able to design new research directions and projects.
- Technical Polyglot: You are comfortable (or eager to become so) at the intersection of ML and computational biology, and eager to collaborate with wet-lab scientists.
- Puzzle Solver: You are excited by solving puzzles that have a translational impact and/or creating new therapeutic approaches.
In this position you will
- Conduct high-impact research: Design, execute, and analyze computational experiments; take end-to-end ownership of a research project within the lab’s scientific focus, with guidance from the PI and increasing independence as you develop expertise.
- Develop as a future scientific leader: Publish first-author papers in high-impact journals, present at national and international conferences, and build a network of collaborators across Arc, Stanford, and beyond.
- Foster scientific excellence: Mentor and train research associates, technicians, and students; engage in Arc-wide activities (seminars, symposia); contribute to a collaborative research environment; maintain rigorous coding standards and documentation; and contribute to lab operations including software development and maintaining shared infrastructure.
Requirements
- Ph.D. in Computer Science, Bioinformatics, Computational Biology, Genetics/Genomics
- Expertise with Python, bash, and standard deep learning frameworks such as PyTorch.
- Excellent written and verbal communication skills.
- Demonstrated ability to work in a fast-paced environment and be both an independent thinker and a highly collaborative team player.
- Track record of creative, high-impact research as demonstrated by publications, patents, developed tools, software etc.
The minimum base salary for this position is $80,000. Base salary for this role is determined by how many months of relevant postdoctoral experience a successful candidate has. Base salary for this role is not negotiable.
About Arc Institute
Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.
Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.
Our two Institute Initiatives reflect this model in action:
- Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets, accelerating the path from biological insight to clinical trials.
- Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.
More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.
About the position
The Hsu Lab is looking for postdoctoral researchers, who are curious, creative and motivated to advance the state-of-the-art in generative AI applied to biology, including Arc’s frontier biological foundation models (Evo, Evo 2, State, Stack, Bioreason, and beyond). The successful candidate is passionate about developing ML models for biological understanding and design, leveraging frontier approaches such as novel ML architectures, post-training, agentic reasoning, and more. Current areas of interest of the lab include building predictive models of life (e.g. by integrating Evo and State), AI agents and systems, genome mining, and invention of new therapeutics through AI-guided approaches.
Postdocs in the lab are encouraged to lead ambitious, independent projects, resulting in high-impact publications. You will have the opportunity to collaborate widely across Arc, Stanford, and the broader Bay Area ecosystem, with access to strong platforms in our lab and our institutions for genomics, single-cell technologies, synthetic biology, high-performance computing clusters, and experimental model systems.
About you
- Extremely Curious & Self-Motivated: You push the boundaries of machine learning, biotechnology, and/or biomedical research.
- High-Velocity Researcher: You thrive in a fast-paced environment and have a bias for action, conducting rigorous and impactful research at scale.
- Intellectually Independent: You are a "first-principles" thinker, able to design new research directions and projects.
- Technical Polyglot: You are comfortable (or eager to become so) at the intersection of ML and computational biology, and eager to collaborate with wet-lab scientists.
- Puzzle Solver: You are excited by solving puzzles that have a translational impact and/or creating new therapeutic approaches.
In this position you will
- Conduct high-impact research: Design, execute, and analyze computational experiments; take end-to-end ownership of a research project within the lab’s scientific focus, with guidance from the PI and increasing independence as you develop expertise.
- Develop as a future scientific leader: Publish first-author papers in high-impact journals, present at national and international conferences, and build a network of collaborators across Arc, Stanford, and beyond.
- Foster scientific excellence: Mentor and train research associates, technicians, and students; engage in Arc-wide activities (seminars, symposia); contribute to a collaborative research environment; maintain rigorous coding standards and documentation; and contribute to lab operations including software development and maintaining shared infrastructure.
Requirements
- Ph.D. in Computer Science, Bioinformatics, Computational Biology, Genetics/Genomics
- Expertise with Python, bash, and standard deep learning frameworks such as PyTorch.
- Excellent written and verbal communication skills.
- Demonstrated ability to work in a fast-paced environment and be both an independent thinker and a highly collaborative team player.
- Track record of creative, high-impact research as demonstrated by publications, patents, developed tools, software etc.
The minimum base salary for this position is $80,000. Base salary for this role is determined by how many months of relevant postdoctoral experience a successful candidate has. Base salary for this role is not negotiable.
See all TN Visa Machine Learning Research Jobs
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Get Access To All JobsTips for Finding TN Visa Sponsorship in Machine Learning Research
Frame your degree for TN eligibility
TN visa officers assess whether your field of study directly supports the role. A degree in computer science, statistics, or applied mathematics maps cleanly to ML Research. A general engineering degree may require a credential evaluation letter to establish the connection.
Target employers experienced with visa sponsorship
Research labs, AI-focused firms, and university spinouts have experience sponsoring work visas for specialized roles. Prioritize roles where the job description specifies a quantitative or computer science degree requirement, since that language directly supports TN eligibility. For Canadians, the employer will provide a support letter you present at the U.S. port of entry; for Mexicans, you'll apply through a U.S. consulate with the employer's support letter.
Search for verified sponsorship opportunities on Migrate Mate
Use Migrate Mate to filter ML Research openings by TN visa sponsorship. It surfaces roles from employers already familiar with the TN process, saving you time spent on positions where sponsorship is uncertain or unavailable.
Clarify your SOC code before the offer letter
Ask your employer to confirm whether the role will be classified under Computer Systems Analyst or a related category. The SOC code shapes the job offer letter language, and a mismatch between the letter and your actual duties is a common TN denial trigger at the port of entry or consulate.
Get your Canadian credentials formatted correctly
Canadian professionals entering by land port need their TN application package ready on arrival. Include your degree transcripts, the employer's offer letter on company letterhead, and a one-page summary of your specific ML Research duties. Officers don't retrieve documents for you.
Prepare for employer unfamiliarity with TN classification
Many U.S. companies default to H-1B visa sponsorship workflows and don't realize TN requires no petition or USCIS filing for Canadians. Come to offer negotiations ready to explain that TN processing is handled at the port of entry or consulate, not through USCIS.
Machine Learning Research TN Visa: Frequently Asked Questions
Does Machine Learning Research qualify as a TN visa occupation?
Yes, but the classification depends on how the role is defined. Most ML Research positions map to Computer Systems Analyst under the USMCA TN category, particularly when the work involves designing or analyzing computational systems. Roles with a stronger mathematical modeling focus may also qualify under Mathematician. The job offer letter must use language that aligns with the qualifying category's duties, not just the job title.
How does TN compare to H-1B for Machine Learning Research roles?
TN is faster and more predictable for Canadian professionals. There's no lottery, no annual cap, and no USCIS petition required. Canadians can be approved at a land port of entry the same day. H-1B involves a lottery with roughly a one-in-four selection rate, a multi-month USCIS process, and a premium processing fee if you need faster results. Mexican nationals still apply through a U.S. consulate, but they also avoid the H-1B lottery entirely.
What documents does my employer need to prepare for my TN application?
Your employer provides a signed offer letter on company letterhead that describes your specific ML Research duties, confirms you'll be employed in a qualifying TN occupation, states your start date and employment terms, and lists your degree requirements for the role. The letter doesn't need to be a formal USCIS filing, but it must be detailed enough for a CBP officer or consular officer to confirm TN eligibility on its face.
Where can I find Machine Learning Research jobs with TN visa sponsorship?
Migrate Mate lets you search ML Research openings filtered specifically by TN visa sponsorship, so you're not guessing which employers will support the process. Many job postings don't specify visa type, and companies that know H-1B often don't realize TN is an option. Filtering by sponsorship type upfront avoids late-stage surprises when you're already in offer discussions.
Can I switch ML Research employers while on TN status?
Yes, but you need a new TN authorization before starting work with the new employer. Canadians can obtain a new TN at a port of entry with the new employer's offer letter. Mexican nationals apply through a U.S. consulate. Unlike H-1B, there's no portability provision that lets you start immediately on a pending application, so time the transition to avoid any gap between your current TN and the new one.