Machine Learning Research Jobs for OPT Students
Machine Learning Research jobs on OPT require STEM designation, which qualifies F-1 students for a 24-month OPT extension beyond the standard 12 months. Most roles sit inside research labs or AI teams at universities, national laboratories, and technology companies, all of which routinely sponsor H-1B and O-1 visas for strong candidates.
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Get Access To All JobsAbout SandboxAQ
SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors.
We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders.
At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.
The Opportunity
The SandboxAQ R&D team is looking for a PostDoc Resident for a 12-month, full-time research opportunity. This role is central to our efforts to bring more AI to the domain of cybersecurity. We are seeking candidates with a strong theoretical background and an interest in frontier research who can apply those foundations and implement them in practice. A successful candidate will be comfortable building models from scratch, fine-tuning existing ones, and designing software systems around those models in close collaboration with our engineering department.
You will be part of a diverse team consisting of ML experts, cryptographers, mathematicians, and physicists. This multidisciplinary group plays a key role in the efficient and effective enablement of cutting-edge technologies being developed at SandboxAQ.
Note: This is a 12-month, full-time fellowship focused on frontier research in a production setting. To see how our fellows contribute to the ecosystem, please learn more about our residency program here.
Key Responsibilities
- Perform exploratory data analysis and feature engineering on vast quantities of data.
- Train models and build agents using the latest machine learning frameworks.
- Integrate research outcomes into the product portfolio by working closely with the engineering team.
- Present your work to broad audiences ranging from academic circles to industry stakeholders.
- Enable cutting-edge technologies effectively as a key contributor to our multidisciplinary R&D environment.
Essential Skills & Experience
- PhD in Machine Learning, Data Science, Computer Science, or a related field with a strong focus on Machine Learning.
- Strong experience in Python and ML frameworks such as Hugging Face Transformers, LangChain, TensorFlow, or PyTorch.
- Successful research track record in the field of Machine Learning.
- Hands-on model development skills, including building models from scratch and running inference efficiently (generative and quantitative).
Highly Desired Skills & Experience
- Agentic Frameworks: Experience with OpenAI agents, Google ADK, or MCP.
- Open Source: Experience contributing to open-source projects.
- Domain Knowledge: Experience in the cybersecurity domain is a plus, but not essential.
Why Join Us?
We offer a comprehensive and competitive benefits package designed to support your health, financial well-being, and life outside of work.
- Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation.
- Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits.
- Work-Life Balance: Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance.
- Career Development: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.
SandboxAQ Welcomes All
We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges.
Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.
Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know.
Read: Guidance for candidates on using AI Tools in interviews.
About SandboxAQ
SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors.
We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders.
At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.
The Opportunity
The SandboxAQ R&D team is looking for a PostDoc Resident for a 12-month, full-time research opportunity. This role is central to our efforts to bring more AI to the domain of cybersecurity. We are seeking candidates with a strong theoretical background and an interest in frontier research who can apply those foundations and implement them in practice. A successful candidate will be comfortable building models from scratch, fine-tuning existing ones, and designing software systems around those models in close collaboration with our engineering department.
You will be part of a diverse team consisting of ML experts, cryptographers, mathematicians, and physicists. This multidisciplinary group plays a key role in the efficient and effective enablement of cutting-edge technologies being developed at SandboxAQ.
Note: This is a 12-month, full-time fellowship focused on frontier research in a production setting. To see how our fellows contribute to the ecosystem, please learn more about our residency program here.
Key Responsibilities
- Perform exploratory data analysis and feature engineering on vast quantities of data.
- Train models and build agents using the latest machine learning frameworks.
- Integrate research outcomes into the product portfolio by working closely with the engineering team.
- Present your work to broad audiences ranging from academic circles to industry stakeholders.
- Enable cutting-edge technologies effectively as a key contributor to our multidisciplinary R&D environment.
Essential Skills & Experience
- PhD in Machine Learning, Data Science, Computer Science, or a related field with a strong focus on Machine Learning.
- Strong experience in Python and ML frameworks such as Hugging Face Transformers, LangChain, TensorFlow, or PyTorch.
- Successful research track record in the field of Machine Learning.
- Hands-on model development skills, including building models from scratch and running inference efficiently (generative and quantitative).
Highly Desired Skills & Experience
- Agentic Frameworks: Experience with OpenAI agents, Google ADK, or MCP.
- Open Source: Experience contributing to open-source projects.
- Domain Knowledge: Experience in the cybersecurity domain is a plus, but not essential.
Why Join Us?
We offer a comprehensive and competitive benefits package designed to support your health, financial well-being, and life outside of work.
- Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation.
- Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits.
- Work-Life Balance: Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance.
- Career Development: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.
SandboxAQ Welcomes All
We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges.
Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.
Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know.
Read: Guidance for candidates on using AI Tools in interviews.
How to Get Visa Sponsorship in Machine Learning Research
Target STEM-designated programs
Verify your degree program carries an approved STEM CIP code before applying. Machine Learning Research roles qualify for the 24-month OPT extension only when your degree field matches the STEM designation list maintained by ICE.
Apply to research-heavy employers first
Universities, national laboratories, and corporate AI research divisions hire ML researchers regularly and have established immigration counsel on staff. These employers understand OPT timelines and are far more likely to sponsor H-1B or O-1 petitions after your authorization period.
Emphasize publications and research output
ML research hiring managers weight peer-reviewed publications, conference papers at NeurIPS, ICML, or ICLR, and open-source model contributions heavily. Strong research output also strengthens future O-1A or EB-1A immigration petitions based on extraordinary ability.
Clarify your authorization window upfront
Tell recruiters your exact EAD expiration date and STEM extension eligibility in the first conversation. Research teams plan hiring timelines months ahead, so knowing you have two to three years of work authorization removes a common sponsorship hesitation early in the process.
Build toward O-1 eligibility from day one
Machine Learning researchers accumulate O-1 qualifying evidence naturally through citations, peer review, judging competitions, and speaking at conferences. Documenting these activities from your first OPT role creates a strong immigration record independent of the H-1B lottery.
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Get Access To All JobsFrequently Asked Questions
Do Machine Learning Research jobs qualify for the 24-month OPT STEM extension?
Yes, provided your underlying degree is in a STEM-designated field such as Computer Science, Statistics, Mathematics, or Electrical Engineering. Machine Learning Research roles fall squarely within the STEM occupation categories that satisfy the extension criteria. You should confirm your specific CIP code with your DSO before filing.
How do I find Machine Learning Research employers that sponsor OPT and H-1B?
Migrate Mate filters job listings specifically for employers willing to sponsor international candidates on OPT, so you can focus your search on companies that have already committed to sponsoring work authorization rather than asking cold. Corporate research labs at large technology companies, university research groups, and federally funded AI institutes are the most active sponsors in this field.
Can I work as an independent or contract ML researcher on OPT?
Self-employment is not permitted on standard OPT. Your work must be directly related to your degree field and performed for an employer who reports your employment to your DSO within 10 days of your start date. Contract or consulting arrangements may be permissible if structured through an employer of record who fulfills the reporting requirement and the work is degree-related.
What happens to my OPT status if my Machine Learning Research position ends before my EAD expires?
OPT allows a cumulative unemployment limit of 90 days during the initial 12-month period and an additional 60 days during the 24-month STEM extension, for 150 days total. Exceeding these limits terminates your F-1 status. If your position ends, you should begin a new job search immediately and report any employment changes to your DSO without delay.
Does Machine Learning Research experience improve my long-term visa sponsorship prospects?
Substantially. Peer-reviewed publications, conference presentations at venues like NeurIPS or ICML, and measurable research impact build direct evidence for O-1A extraordinary ability petitions and EB-1A or EB-2 NIW green card categories. Employers in this field are also among the most experienced H-1B sponsors, meaning your transition from OPT to long-term status is a well-established path rather than an exception.
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