H-1B Visa AI ML Platform Jobs
AI ML Platform roles sit squarely within H-1B visa specialty occupation territory, requiring at least a bachelor's degree in computer science, machine learning, or a closely related field. Employers filing LCAs for these positions routinely appear in DOL disclosure data, making sponsorship history verifiable before you apply.
Find H-1B Visa AI ML Platform JobsOverview
Showing 5 of 1,113+ AI ML Platform jobs
See all 1,113+ AI ML Platform Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI ML Platform roles.
Get Access To All JobsZoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in ML and CV to make autonomous driving as seamless as possible.
The Opportunity
Would you like to be part of the ML Training platform team that enables autonomous driving, driving scenario understanding, learned planning and trajectories, large scale driving simulations and several other ML use cases at Zoox? You will get to work across all ML teams within Zoox - Foundation Models, Perception, Prediction, Planner, Simulation, Data Science, Collision Avoidance, etc. and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox.
The ML Training platform team builds and operates the core part of the ML platform that powers model training at scale. We are responsible for developing and operating ML tools, deep learning frameworks, and distributed model training infrastructure to support foundational models and reinforcement learning. This team also owns the model repository and model lifecycle management tools used by our applied research teams for in- and off-vehicle ML use cases. You will play a crucial role in reducing the time it takes from ideation to productionization of cutting-edge AI innovation. This team has a lot of growth opportunities as we expand our robotaxi deployments and venture into new ML domains.
In this role, you will:
- Build the Zoox Training framework leveraged by all ML teams within Zoox. This framework needs to be highly scalable, reliable, and efficient.
- Design, implement, and operate a robust and efficient ML platform to enable the training, validation, serving, and monitoring of ML models.
- Collaborate closely with cross-functional teams, including ML researchers, software engineers, and data engineers, to define requirements and align on architectural decisions.
Qualifications
- 2+ years of ML infrastructure experience.
- Experience with training frameworks like PyTorch, DeepSpeed, JAX, Ray, etc.
- Experience working with cloud providers like AWS.
Bonus Qualifications
- Experience with building large-scale, cost-efficient distributed model training and ML compute infrastructure.
- Experience with building model lifecycle management tools and experimentation.
Base Salary Range
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
Accommodations
If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.
A Final Note: You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in ML and CV to make autonomous driving as seamless as possible.
The Opportunity
Would you like to be part of the ML Training platform team that enables autonomous driving, driving scenario understanding, learned planning and trajectories, large scale driving simulations and several other ML use cases at Zoox? You will get to work across all ML teams within Zoox - Foundation Models, Perception, Prediction, Planner, Simulation, Data Science, Collision Avoidance, etc. and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox.
The ML Training platform team builds and operates the core part of the ML platform that powers model training at scale. We are responsible for developing and operating ML tools, deep learning frameworks, and distributed model training infrastructure to support foundational models and reinforcement learning. This team also owns the model repository and model lifecycle management tools used by our applied research teams for in- and off-vehicle ML use cases. You will play a crucial role in reducing the time it takes from ideation to productionization of cutting-edge AI innovation. This team has a lot of growth opportunities as we expand our robotaxi deployments and venture into new ML domains.
In this role, you will:
- Build the Zoox Training framework leveraged by all ML teams within Zoox. This framework needs to be highly scalable, reliable, and efficient.
- Design, implement, and operate a robust and efficient ML platform to enable the training, validation, serving, and monitoring of ML models.
- Collaborate closely with cross-functional teams, including ML researchers, software engineers, and data engineers, to define requirements and align on architectural decisions.
Qualifications
- 2+ years of ML infrastructure experience.
- Experience with training frameworks like PyTorch, DeepSpeed, JAX, Ray, etc.
- Experience working with cloud providers like AWS.
Bonus Qualifications
- Experience with building large-scale, cost-efficient distributed model training and ML compute infrastructure.
- Experience with building model lifecycle management tools and experimentation.
Base Salary Range
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
Accommodations
If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.
A Final Note: You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
See all 1,113+ H-1B Visa AI ML Platform Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa AI ML Platform Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship in AI ML Platform
Verify your SOC code before interviewing
AI ML Platform roles typically file under SOC 15-1244 (Software Developers) or 15-2051 (Data Scientists). Confirm which code your prospective employer used on past LCAs so your degree field aligns with the specialty occupation definition USCIS will evaluate.
Pull employer LCA history on Migrate Mate
Search AI ML Platform roles on Migrate Mate to see which companies have active DOL Labor Condition Applications for this job category. Employers with recent LCA filings have already cleared the prevailing-wage certification step, reducing your offer-to-petition timeline.
Check prevailing wage before negotiating your offer
Use the OFLC Wage Search to look up the Level I through Level IV wage for your SOC code and work location ZIP code. Your offered salary must meet or exceed the certified wage, so knowing the floor before negotiation prevents offer rescissions at the LCA stage.
Document platform engineering contributions specifically
USCIS RFEs for ML platform roles often challenge whether the position requires a specific degree rather than any bachelor's. Organize portfolio evidence around distributed training infrastructure, model serving architecture, or MLOps pipeline design, all of which map to a computer science or engineering degree field.
Target cap-exempt employers if the lottery is a risk
Universities, nonprofit research organizations, and government-affiliated entities are cap-exempt, meaning they can file H-1B petitions year-round with no lottery exposure. AI and ML platform work exists at these institutions, particularly in research computing and scientific infrastructure teams.
Request premium processing before your OPT expires
USCIS adjudicates premium processing petitions within 15 business days. If your OPT end date is within 90 days of the April 1 filing window, ask your employer to elect premium processing so you have an approval or RFE response before your authorization lapses.
H-1B Visa AI ML Platform: Frequently Asked Questions
Does an AI ML Platform role qualify as a specialty occupation for H-1B purposes?
Yes, provided the job description requires at minimum a bachelor's degree in a specific technical field such as computer science, electrical engineering, or mathematics. Roles focused on ML infrastructure, distributed training systems, or model deployment pipelines routinely satisfy this standard. If the posting says a degree is preferred rather than required, the employer should revise the job requirements before filing the LCA with DOL.
Which employers sponsor H-1B visas for AI ML Platform jobs?
Large cloud providers, enterprise software companies, financial institutions with quantitative engineering teams, and well-funded AI startups regularly file LCAs for ML platform roles. Migrate Mate surfaces employers with verified DOL Labor Condition Application history for this job category, so you can filter your search to companies that have already demonstrated sponsorship activity rather than guessing from job postings.
Can I transfer my H-1B to a new AI ML Platform employer mid-status?
Yes. Under H-1B portability, you can start working for a new employer as soon as the transfer petition is filed with USCIS, without waiting for approval, as long as your prior H-1B was approved and you've maintained valid status. The new employer must file a new I-129 and obtain a fresh LCA from DOL certified to their worksite location and the applicable prevailing wage.
How does the H-1B prevailing wage apply to remote AI ML Platform roles?
The prevailing wage is tied to the worksite location listed on the LCA, not where the company is headquartered. For fully remote roles, DOL requires the employer to list your home address as the worksite and certify the prevailing wage for that location. If you relocate mid-employment, the employer may need to file an amended LCA and petition reflecting the new worksite. Use the OFLC Wage Search to check the wage floor for your home location before accepting a remote offer.
What happens to my H-1B status if my AI ML Platform role changes significantly after approval?
Material changes to job duties, salary, or worksite that fall outside the scope of the approved petition require an amended H-1B petition before the changes take effect. Moving from an individual contributor role to a team lead position with meaningfully different duties, or shifting from one SOC occupation code to another, typically triggers an amendment filing. USCIS evaluates whether the amended role still satisfies specialty occupation requirements under the original or a new LCA.