Machine Learning Engineer Jobs for OPT Students
Machine Learning Engineer roles are among the most OPT-friendly positions in tech, with high demand from employers already familiar with F-1 work authorization. Most roles qualify as STEM OPT, giving you up to 36 months of work authorization, and many employers actively file H-1B petitions for strong ML candidates.
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Get Access To All JobsABOUT OUMI
Why we exist: Oumi is on a mission to make frontier AI truly open for all. We are founded on the belief that AI will have a transformative impact on humanity, and that developing it collectively, in the open, is the best path forward to ensure that it is done efficiently and safely. By providing the safest, highest quality, and most flexible AI, we aspire to unlock positive impact for every individual, enterprise, and humanity overall.
What we do: Oumi provides an all-in-one platform to build state-of-the-art AI models, end to end; from data preparation to model training, evaluation and production deployment, empowering innovators to build cutting-edge models at any scale. Oumi also advances open foundation models in collaboration with academic collaborators and the open community.
Our Approach: Oumi is built on a foundation of open source, with open collaboration at the heart of everything we do. Our work is:
- Research-driven: We conduct and publish original AI research, working closely with academic research labs and collaborators across the globe.
- Community-powered: We believe in the strength of open collaboration and actively welcome contributions from researchers and developers worldwide.
- Accessibility-focused: We design Oumi to help any organization—regardless of size or resources—effectively build, deploy, and benefit from AI by lowering barriers to access, experimentation, and adoption.
ROLE OVERVIEW
We’re looking for our first Pre/Post-Sales Machine Learning Engineer who bridges the gap between technical expertise and customer success. You’ll work closely with our customers to design, train, and deploy AI models using Oumi’s platform. This role blends solution architecture, applied machine learning, and customer interaction - ideal for someone who loves both building systems and helping others use them effectively.
You’ll play an important role in shaping not only the direction of the team but also the product. You will collaborate closely with research, product, and engineering teams to ensure customers have a world-class experience using Oumi, while channeling feedback to improve our platform.
YOU WILL:
- Drive success with customers: Partner with customers through the pre-sales and post-sales lifecycle - from technical demos and proof-of-concept design to hands-on training and deploying models.
- Create custom models: Train, fine-tune, and evaluate modern LLMs and other AI models using Oumi’s platform.
- Design AI solution architectures: Work with customers to design scalable ML workflows using best practices in data preparation, training, and deployment.
- Be a technical advocate: Help customers understand Oumi’s capabilities, providing technical insight and translating research innovations into practical solutions.
- Drive product improvements: Work closely with the product and research teams to surface customer needs and help shape the future of Oumi’s platform.
- Educate & Enable: Develop technical guides, demos, and best practices to help customers and the open community succeed with Oumi.
WHAT YOU’LL BRING:
- Experience: You have 4+ years of experience in applied ML, ML infrastructure, or solution/sales engineering roles.
- ML Expertise: You bring a solid understanding of machine learning workflows, with experience training or fine-tuning modern foundation models (e.g., LLMs, diffusion models, multimodal systems).
- Development Skills: You are proficient in Python with a strong understanding of AI/LLM best practices including practical experience with model training frameworks and using LLMs in production environments for modern use cases (e.g. RAG, agents, or agentic systems).
- Customer-Facing Strength: You have strong experience communicating complex technical concepts clearly and empathetically to both technical and non-technical audiences.
- Learners Mindset: You can proactively address gaps in your understanding of concepts and are willing to pick up whatever knowledge you're missing to get the job done.
- Operational Excellence: You can operate in and manage ambiguity while owning problems end-to-end.
- Values: You embody Oumi's core values: Beneficial for All, Customer-Ossessed, Radical Ownership, Exceptional Teammates, Science-Grounded.
BENEFITS:
- Equity in a high-growth startup
- Comprehensive health, dental, and vision insurance
- 21 days PTO
- Regular team offsites and events
LOCATION:
- Remote OR hybrid work environment, with offices in:
- San Mateo, CA
- Seattle, WA
- New York, NY
ABOUT OUMI
Why we exist: Oumi is on a mission to make frontier AI truly open for all. We are founded on the belief that AI will have a transformative impact on humanity, and that developing it collectively, in the open, is the best path forward to ensure that it is done efficiently and safely. By providing the safest, highest quality, and most flexible AI, we aspire to unlock positive impact for every individual, enterprise, and humanity overall.
What we do: Oumi provides an all-in-one platform to build state-of-the-art AI models, end to end; from data preparation to model training, evaluation and production deployment, empowering innovators to build cutting-edge models at any scale. Oumi also advances open foundation models in collaboration with academic collaborators and the open community.
Our Approach: Oumi is built on a foundation of open source, with open collaboration at the heart of everything we do. Our work is:
- Research-driven: We conduct and publish original AI research, working closely with academic research labs and collaborators across the globe.
- Community-powered: We believe in the strength of open collaboration and actively welcome contributions from researchers and developers worldwide.
- Accessibility-focused: We design Oumi to help any organization—regardless of size or resources—effectively build, deploy, and benefit from AI by lowering barriers to access, experimentation, and adoption.
ROLE OVERVIEW
We’re looking for our first Pre/Post-Sales Machine Learning Engineer who bridges the gap between technical expertise and customer success. You’ll work closely with our customers to design, train, and deploy AI models using Oumi’s platform. This role blends solution architecture, applied machine learning, and customer interaction - ideal for someone who loves both building systems and helping others use them effectively.
You’ll play an important role in shaping not only the direction of the team but also the product. You will collaborate closely with research, product, and engineering teams to ensure customers have a world-class experience using Oumi, while channeling feedback to improve our platform.
YOU WILL:
- Drive success with customers: Partner with customers through the pre-sales and post-sales lifecycle - from technical demos and proof-of-concept design to hands-on training and deploying models.
- Create custom models: Train, fine-tune, and evaluate modern LLMs and other AI models using Oumi’s platform.
- Design AI solution architectures: Work with customers to design scalable ML workflows using best practices in data preparation, training, and deployment.
- Be a technical advocate: Help customers understand Oumi’s capabilities, providing technical insight and translating research innovations into practical solutions.
- Drive product improvements: Work closely with the product and research teams to surface customer needs and help shape the future of Oumi’s platform.
- Educate & Enable: Develop technical guides, demos, and best practices to help customers and the open community succeed with Oumi.
WHAT YOU’LL BRING:
- Experience: You have 4+ years of experience in applied ML, ML infrastructure, or solution/sales engineering roles.
- ML Expertise: You bring a solid understanding of machine learning workflows, with experience training or fine-tuning modern foundation models (e.g., LLMs, diffusion models, multimodal systems).
- Development Skills: You are proficient in Python with a strong understanding of AI/LLM best practices including practical experience with model training frameworks and using LLMs in production environments for modern use cases (e.g. RAG, agents, or agentic systems).
- Customer-Facing Strength: You have strong experience communicating complex technical concepts clearly and empathetically to both technical and non-technical audiences.
- Learners Mindset: You can proactively address gaps in your understanding of concepts and are willing to pick up whatever knowledge you're missing to get the job done.
- Operational Excellence: You can operate in and manage ambiguity while owning problems end-to-end.
- Values: You embody Oumi's core values: Beneficial for All, Customer-Ossessed, Radical Ownership, Exceptional Teammates, Science-Grounded.
BENEFITS:
- Equity in a high-growth startup
- Comprehensive health, dental, and vision insurance
- 21 days PTO
- Regular team offsites and events
LOCATION:
- Remote OR hybrid work environment, with offices in:
- San Mateo, CA
- Seattle, WA
- New York, NY
How to Get Visa Sponsorship as a Machine Learning Engineer
Target companies with active H-1B filing histories
Large tech firms and well-funded AI startups file H-1B petitions regularly for ML roles. Filtering by employers with consistent sponsorship track records is the most reliable way to avoid wasting applications on companies that won't convert your OPT.
Lead with your research output and production deployments
Employers sponsoring ML engineers want evidence of real impact. Published papers, Kaggle rankings, open-source contributions, and deployed models in production all signal the kind of technical depth that makes sponsorship worth the investment for a hiring manager.
Apply before your OPT start date, not after
Most ML hiring pipelines take six to twelve weeks from application to offer. Starting your search three to four months before your OPT authorization date gives employers enough runway to complete interviews and onboarding before your work authorization begins.
Clarify your STEM OPT extension eligibility upfront
ML Engineering consistently qualifies under STEM OPT CIP codes tied to computer science and data science programs. Confirming your degree program qualifies before interviews prevents late-stage confusion and reassures employers that 36 months of authorization is on the table.
Specialize in a high-demand ML subfield
Employers sponsoring visas need strong justification for the cost. Specializing in LLM fine-tuning, computer vision, or MLOps makes you a clearer candidate for roles that are genuinely hard to fill, which strengthens the business case for sponsorship.
Negotiate H-1B filing into your offer conversation early
Bringing up sponsorship after receiving an offer creates friction. Raising it naturally during late-stage interviews, once the employer is clearly interested, lets you confirm their willingness to file before you invest further time in the process.
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Get Access To All JobsFrequently Asked Questions
Do Machine Learning Engineer jobs typically qualify for STEM OPT extension?
Yes. Machine Learning Engineering falls under CIP codes tied to computer science, data science, and electrical engineering programs, all of which are on the STEM Designated Degree Program list. If your degree is in one of those fields, you're eligible to apply for the 24-month STEM OPT extension, giving you up to 36 months of total work authorization.
How do I find Machine Learning Engineer jobs where the employer is willing to sponsor OPT and H-1B?
Migrate Mate filters jobs specifically for F-1 OPT students, so the roles listed are from employers familiar with or actively open to sponsorship. Browsing ML Engineer listings on Migrate Mate saves significant time compared to filtering through general job boards where most postings don't address visa sponsorship at all.
Can I work as a Machine Learning Engineer on OPT before my STEM extension is approved?
Yes, as long as your initial 12-month OPT authorization is active and you've submitted your STEM OPT extension application before it expires. USCIS automatically extends your work authorization by up to 180 days while the extension is pending, so there's no gap in your ability to work, provided you filed on time.
What employment relationship counts as valid for STEM OPT in an ML role?
STEM OPT requires a formal employer-employee relationship, meaning your employer must provide supervision, control your work schedule, and report training outcomes through the SEVP portal. Fully independent contracting arrangements do not satisfy this requirement. Most full-time ML Engineering positions at tech companies meet the standard, but contract-to-hire roles should be reviewed with your DSO before accepting.
Do employers need to pay OPT students market rate for Machine Learning Engineer roles?
STEM OPT regulations require that employers pay OPT students the same wages and working conditions offered to similarly situated U.S. workers in the same role and location. For ML Engineering, which commands strong compensation across the industry, this protection matters. If an employer offers terms noticeably below what comparable full-time employees receive, that arrangement likely doesn't comply with STEM OPT requirements.
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