OPT Artificial Intelligence Scientist Jobs
Artificial Intelligence Scientist roles are among the most OPT-friendly positions in tech, with the majority of employers already familiar with H-1B visa sponsorship pipelines. STEM OPT extension eligibility gives you up to three years of work authorization, making you a competitive candidate at research labs, AI-focused startups, and large tech companies.
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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 660+ OPT Artificial Intelligence Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new OPT Artificial Intelligence Scientist Jobs.
Get Access To All JobsTips for Finding OPT Sponsorship as an Artificial Intelligence Scientist
Target STEM-designated programs first
Your CIP code must fall under an approved STEM field to qualify for the 24-month extension. Confirm your degree classification with your DSO before applying, since some AI and data science programs were added to the STEM list recently.
Prioritize employers with active H-1B filing history
Companies that have sponsored H-1B visa petitions for AI scientists are significantly more likely to continue doing so. Research employer sponsorship patterns before investing time in applications, rather than relying on job postings alone to signal willingness.
Frame your research experience around applied impact
Hiring managers at companies that sponsor visas want to see how your research translates to production systems. Quantify model performance improvements, deployment outcomes, or compute efficiency gains in your resume to stand out in technical screening rounds.
Apply to national labs and R&D-heavy employers
Federal contractors and national research laboratories frequently hire AI scientists and have established processes for sponsoring work visas. These roles often align closely with advanced degree backgrounds and value publications, patents, and domain specialization over broad industry experience.
Start your job search at least six months before OPT expires
H-1B cap-subject petitions must be filed by April 1 for an October 1 start date. If your OPT ends before October, you may need a cap-exempt employer or a bridge strategy, so early planning matters significantly.
Highlight publications and open-source contributions
AI scientist roles are highly credential-driven. Listing peer-reviewed papers, conference presentations at NeurIPS or ICML, or significant open-source model contributions signals the kind of specialized expertise that justifies a visa sponsorship investment to hiring teams.
Artificial Intelligence Scientist OPT: Frequently Asked Questions
Do Artificial Intelligence Scientist roles qualify for the STEM OPT extension?
Yes, in nearly all cases. AI scientist positions require a degree in computer science, statistics, mathematics, or a closely related STEM field, all of which qualify for the 24-month STEM OPT extension. That gives you up to three years of total OPT work authorization, which is one of the primary reasons AI roles are attractive to F-1 students navigating post-graduation work authorization.
How many employers actively sponsor AI Scientists for H-1B visas?
A substantial number do. Large technology companies, AI-native startups, financial institutions with quantitative research teams, and national research laboratories all have established H-1B sponsorship processes and regularly hire for AI scientist roles. Migrate Mate filters specifically for OPT-friendly and sponsoring employers, so you can focus your search on companies that have already demonstrated willingness to sponsor rather than guessing from job descriptions.
Can I work as an AI Scientist on OPT before the H-1B lottery?
Yes. You can begin working as soon as your OPT authorization starts, and you can continue on STEM OPT extension while your employer files an H-1B petition. If selected in the lottery, your H-1B takes effect October 1. If not selected, you can remain on STEM OPT until it expires, giving your employer multiple lottery cycles to try again.
What degree fields count as qualifying STEM for AI Scientist OPT?
Computer science, electrical engineering, applied mathematics, statistics, cognitive science, and data science are all on the approved STEM CIP code list. Some newer AI-specific degree programs may also qualify. Your DSO at your university can confirm whether your specific program is designated as STEM, which is the key eligibility requirement for the extension.
Is a PhD required to get visa sponsorship as an AI Scientist?
Not always, though a PhD significantly strengthens your candidacy for research-focused roles and makes the H-1B specialty occupation case easier to establish. Many industry AI scientist positions accept candidates with a master's degree plus strong research experience or publications. The role title and duties matter more than the degree level when employers assess whether sponsorship is viable for a specific position.