OPT Generative AI Engineer Jobs
Generative AI Engineer jobs are among the most actively sponsored OPT roles in tech right now. Employers filing H-1B visa petitions for this title have surged over the past two years, making it a strong fit for F-1 students on STEM OPT extensions. Most roles qualify under computer science or electrical engineering degree fields.
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Amazon Lab126 builds the synthetic data that trains the AI in Amazon's devices, spanning wearables, smart home, and streaming. The team is looking for Applied Scientists to advance the science of making synthetic data maximally useful to the models it trains, across video, audio, and 3D. This is generation, but it is also the full loop around it: deciding what data to generate through data-centric methods like importance sampling and curriculum design, combining it with real data, and measuring its effect on the models that ship to customers.
A large part of the opportunity lies in the physical environment and how it responds to activity around it, including fast-moving, rule-governed events where signals across modalities must stay aligned in space and time. You will develop generative and simulation methods, from diffusion and multimodal models to physics-based digital twins and sim-to-real transfer, grounded in precise 3D spatial understanding, and deliver science artifacts that feed the models shipping in Amazon's devices. This is a hands-on research role with technical lead scope, reporting to a manager within a cross-discipline organization of Applied Scientists and Software Development Engineers.
Key job responsibilities
- Develop and fine-tune generative models and 3D simulation pipelines across video, audio, and sensor modalities, advancing temporal coherence, identity preservation, controllability, and causality so that generation is action-conditioned and physically plausible.
- Develop training recipes that combine synthetic and real data effectively, including mixing ratios, curriculum ordering, and sampling strategies, and characterize when synthetic data helps, when it hurts, and why.
- Build evaluation methods that predict synthetic data's impact on downstream models without full training runs, using proxy signals and embedding-based diagnostics that shorten the feedback loop from days to minutes.
- Model structured, rule-governed activity so that generated multimodal data stays coherent across modalities, 3D space, and time, and build 3D-consistent scene and event representations that keep generated data spatially faithful.
- Validate all work by measured improvement on production models, ship science artifacts to products, and mentor junior scientists and interns.
A day in the life
You might start your morning reviewing experiment results from an overnight training run, then join a design discussion with engineers to plan how your model will be integrated into a production pipeline. After lunch, you could be prototyping a new approach to a problem your team recently identified, writing clean and well-documented code as you iterate. Later, you might pair with a teammate to review their research methodology or prepare findings for an upcoming science review.
About the team
Our team owns the synthetic data strategy that accelerates time to market across Amazon's devices business. Demand for this data is growing, and we are actively expanding into new product categories. Our goal is to own this strategy across multiple flagship product lines for the entire devices organization, dramatically reducing how long it takes to get new capabilities into customers' hands.
We are a cross-discipline group of Applied Scientists and Software Development Engineers who partner closely to move ideas from research to production. If you want your science to directly shape the AI powering the next generation of Amazon devices, this is an exciting place to build your career.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms
- 2+ years of building machine learning models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience in designing experiments and statistical analysis of results
PREFERRED QUALIFICATIONS
- Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow
- Have publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, CA, Sunnyvale - 171,600.00 - 222,200.00 USD annually
USA, WA, Bellevue - 142,800.00 - 193,200.00 USD annually
DESCRIPTION
Amazon Lab126 builds the synthetic data that trains the AI in Amazon's devices, spanning wearables, smart home, and streaming. The team is looking for Applied Scientists to advance the science of making synthetic data maximally useful to the models it trains, across video, audio, and 3D. This is generation, but it is also the full loop around it: deciding what data to generate through data-centric methods like importance sampling and curriculum design, combining it with real data, and measuring its effect on the models that ship to customers.
A large part of the opportunity lies in the physical environment and how it responds to activity around it, including fast-moving, rule-governed events where signals across modalities must stay aligned in space and time. You will develop generative and simulation methods, from diffusion and multimodal models to physics-based digital twins and sim-to-real transfer, grounded in precise 3D spatial understanding, and deliver science artifacts that feed the models shipping in Amazon's devices. This is a hands-on research role with technical lead scope, reporting to a manager within a cross-discipline organization of Applied Scientists and Software Development Engineers.
Key job responsibilities
- Develop and fine-tune generative models and 3D simulation pipelines across video, audio, and sensor modalities, advancing temporal coherence, identity preservation, controllability, and causality so that generation is action-conditioned and physically plausible.
- Develop training recipes that combine synthetic and real data effectively, including mixing ratios, curriculum ordering, and sampling strategies, and characterize when synthetic data helps, when it hurts, and why.
- Build evaluation methods that predict synthetic data's impact on downstream models without full training runs, using proxy signals and embedding-based diagnostics that shorten the feedback loop from days to minutes.
- Model structured, rule-governed activity so that generated multimodal data stays coherent across modalities, 3D space, and time, and build 3D-consistent scene and event representations that keep generated data spatially faithful.
- Validate all work by measured improvement on production models, ship science artifacts to products, and mentor junior scientists and interns.
A day in the life
You might start your morning reviewing experiment results from an overnight training run, then join a design discussion with engineers to plan how your model will be integrated into a production pipeline. After lunch, you could be prototyping a new approach to a problem your team recently identified, writing clean and well-documented code as you iterate. Later, you might pair with a teammate to review their research methodology or prepare findings for an upcoming science review.
About the team
Our team owns the synthetic data strategy that accelerates time to market across Amazon's devices business. Demand for this data is growing, and we are actively expanding into new product categories. Our goal is to own this strategy across multiple flagship product lines for the entire devices organization, dramatically reducing how long it takes to get new capabilities into customers' hands.
We are a cross-discipline group of Applied Scientists and Software Development Engineers who partner closely to move ideas from research to production. If you want your science to directly shape the AI powering the next generation of Amazon devices, this is an exciting place to build your career.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms
- 2+ years of building machine learning models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience in designing experiments and statistical analysis of results
PREFERRED QUALIFICATIONS
- Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow
- Have publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, CA, Sunnyvale - 171,600.00 - 222,200.00 USD annually
USA, WA, Bellevue - 142,800.00 - 193,200.00 USD annually
See all OPT Generative AI Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new OPT Generative AI Engineer Jobs.
Get Access To All JobsTips for Finding OPT Sponsorship as a Generative AI Engineer
Target companies with active LCA filings
Employers who have filed Labor Condition Applications for AI or machine learning roles in the past 12 months are far more likely to sponsor again. This filing history is public record and signals genuine sponsorship infrastructure, not just intent.
Lead with your model fine-tuning experience
Hiring managers for generative AI roles prioritize hands-on work with large language models. Specify the models you've fine-tuned, the frameworks you used, and the downstream tasks your work improved. Vague AI experience won't move your resume forward.
Clarify your OPT timeline upfront with recruiters
STEM OPT gives you up to three years of work authorization. Telling recruiters your exact end date and H-1B visa eligibility window removes ambiguity and helps them assess sponsorship timing before investing in interviews.
Prioritize startups backed by major AI investors
Well-funded AI startups often move faster on sponsorship decisions than large enterprises. Companies backed by established venture firms typically have legal counsel already familiar with H-1B filings for engineering roles.
Build a public portfolio of generative AI projects
A GitHub repository or demo application showing retrieval-augmented generation, prompt engineering, or multimodal model work gives hiring managers something concrete to evaluate before your interview, which reduces perceived sponsorship risk.
Frame your degree field precisely on applications
Generative AI Engineer roles qualify as specialty occupations under computer science, electrical engineering, or mathematics. State your degree field explicitly on applications and in interviews so employers understand the OPT authorization is already well-established for this role.
Generative AI Engineer OPT: Frequently Asked Questions
Do Generative AI Engineer roles qualify for STEM OPT extension?
Yes. Generative AI Engineer positions fall under CIP codes tied to computer science, electrical engineering, and related STEM fields, which are all on the STEM OPT designated degree program list. If your degree is in one of those fields, you're eligible for the 24-month STEM OPT extension on top of your initial 12-month OPT period, giving you up to three years of work authorization.
How hard is it to find a Generative AI Engineer job that sponsors OPT?
Generative AI is one of the fastest-growing engineering disciplines, and employer demand has outpaced domestic supply consistently over the past two years. Many companies actively recruiting for these roles already have H-1B sponsorship infrastructure in place. Migrate Mate filters job listings specifically for OPT-sponsoring employers, so you're not wading through postings that will reject you at the authorization question.
What degree fields support OPT authorization for Generative AI Engineer roles?
Computer science, electrical engineering, mathematics, statistics, and data science degrees all commonly support OPT authorization for generative AI positions. USCIS evaluates whether a direct relationship exists between your degree field and the job duties. For generative AI roles involving model training, fine-tuning, and deployment, computer science and electrical engineering degrees have the clearest precedent.
Can I work as a Generative AI Engineer at a startup on OPT?
Yes, with one important caveat: the employer must sign your STEM OPT I-983 training plan and meet the E-Verify requirement. Startups are eligible sponsors as long as they're enrolled in E-Verify. Many well-funded AI startups already meet this requirement. Confirm E-Verify enrollment before accepting an offer, because without it your STEM OPT extension cannot be authorized.
What should I look for in a Generative AI Engineer job posting to assess sponsorship likelihood?
Look for explicit H-1B or OPT sponsorship language in the posting, E-Verify enrollment, and prior LCA filings for similar roles. Companies that mention visa sponsorship availability, even briefly, are signaling existing infrastructure. Postings that say 'must be authorized to work without sponsorship' are disqualifying. Filtering by sponsorship-open employers from the start saves significant time.