J-1 Visa AI Platform Engineer Jobs
AI Platform Engineer roles in the United States are accessible to international professionals through J-1 visa sponsorship under the Trainee or Research Scholar program category. A U.S. Department of State-designated sponsor organization issues your DS-2019, while the tech company or research institution serves as your host employer.
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Get Access To All JobsWho We Are
Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale—empowering a safer, richer, and more connected future.
About The Role
As a software engineering intern, you will work closely with leading experts in the field of machine learning, robotics, and software. Depending on your skill sets and areas of interest, you will work on some or all of the following: Data Platform, Onboard Systems, ML Infrastructure, Simulation, or Technical Infrastructure teams.
About The Work
Depending on your skill set and areas of interest you will work on some or all of the following:
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Data Platform: The Data Platform serves as a comprehensive management system for Nuro AI Driver's data, labels, and metrics, facilitating seamless access functionality. The team focuses on data annotation across various domains, including 2D/3D perception, mapping, behavior trajectory, and language/text. It also handles data ingestion and mining, employing methods such as heuristics and embedding search. Additionally, the platform supports the autonomy evaluation infrastructure by providing detailed introspection.
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Onboard Systems: Our onboard system team’s software engineers provide a reliable and high-performance platform that allows our autonomy teams to integrate their autonomy software and algorithms that work across various self-driving platforms. This work requires close collaboration with our software teams, hardware teams, and systems/safety team to make sure new software and hardware work together safely and reliably and resolve onboard error and performance problems.
-
ML Infrastructure: The ML Infra team is the accelerator to our ML-first autonomy strategy. This team provides solutions to empower machine learning development in Nuro and optimize on-cloud training and onboard inference. Our solutions include a distributed training platform, ML compiler, model components libraries, etc. The team provides opportunities for infra engineers to work fully embedded in ML teams to build cutting edge deep learning technologies.
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Simulation: The Simulation team builds the simulator that allows us to develop and test our autonomous driving technology in a virtual setting. We work on the core simulator and simulation frameworks, sensor simulation, scenario generation, and solutions that combine real-world data with synthetic techniques to push the boundaries of what can be simulated, collaborating closely with teams across Autonomy and AI Platform to allow us to simulate realistically and reliably at scale.
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Technical Infrastructure: This group owns few fundamental services for entire engineering organizations: generic compute platform to host mission-critical workflows such as data processing and simulation, storage management service which manages hundreds of PB of data, cloud infrastructure serves as IaaC which provisions and maintains all cloud resources, engineering productivity provides tools such as build and CI/CD to make engineering work more efficient.
About You
You have deep expertise and prior experience in some or many of the following areas:
- You are a current BS or MS candidate in Computer Science, Electrical Engineering, Robotics, or a related field graduating in December 2026 or later
- You have experience in one or more of the following areas: backend API design, applications development, large-scale distributed systems; data storage and processing systems; advanced algorithms using C++ and Python; machine learning, multithreading; x86 architecture; and software performance tuning and optimization, robotics software frameworks, different compute modalities (CPU, GPU, FPGA) etc.
- You have strong problem solving and programming skills.
At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics.
Who We Are
Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale—empowering a safer, richer, and more connected future.
About The Role
As a software engineering intern, you will work closely with leading experts in the field of machine learning, robotics, and software. Depending on your skill sets and areas of interest, you will work on some or all of the following: Data Platform, Onboard Systems, ML Infrastructure, Simulation, or Technical Infrastructure teams.
About The Work
Depending on your skill set and areas of interest you will work on some or all of the following:
-
Data Platform: The Data Platform serves as a comprehensive management system for Nuro AI Driver's data, labels, and metrics, facilitating seamless access functionality. The team focuses on data annotation across various domains, including 2D/3D perception, mapping, behavior trajectory, and language/text. It also handles data ingestion and mining, employing methods such as heuristics and embedding search. Additionally, the platform supports the autonomy evaluation infrastructure by providing detailed introspection.
-
Onboard Systems: Our onboard system team’s software engineers provide a reliable and high-performance platform that allows our autonomy teams to integrate their autonomy software and algorithms that work across various self-driving platforms. This work requires close collaboration with our software teams, hardware teams, and systems/safety team to make sure new software and hardware work together safely and reliably and resolve onboard error and performance problems.
-
ML Infrastructure: The ML Infra team is the accelerator to our ML-first autonomy strategy. This team provides solutions to empower machine learning development in Nuro and optimize on-cloud training and onboard inference. Our solutions include a distributed training platform, ML compiler, model components libraries, etc. The team provides opportunities for infra engineers to work fully embedded in ML teams to build cutting edge deep learning technologies.
-
Simulation: The Simulation team builds the simulator that allows us to develop and test our autonomous driving technology in a virtual setting. We work on the core simulator and simulation frameworks, sensor simulation, scenario generation, and solutions that combine real-world data with synthetic techniques to push the boundaries of what can be simulated, collaborating closely with teams across Autonomy and AI Platform to allow us to simulate realistically and reliably at scale.
-
Technical Infrastructure: This group owns few fundamental services for entire engineering organizations: generic compute platform to host mission-critical workflows such as data processing and simulation, storage management service which manages hundreds of PB of data, cloud infrastructure serves as IaaC which provisions and maintains all cloud resources, engineering productivity provides tools such as build and CI/CD to make engineering work more efficient.
About You
You have deep expertise and prior experience in some or many of the following areas:
- You are a current BS or MS candidate in Computer Science, Electrical Engineering, Robotics, or a related field graduating in December 2026 or later
- You have experience in one or more of the following areas: backend API design, applications development, large-scale distributed systems; data storage and processing systems; advanced algorithms using C++ and Python; machine learning, multithreading; x86 architecture; and software performance tuning and optimization, robotics software frameworks, different compute modalities (CPU, GPU, FPGA) etc.
- You have strong problem solving and programming skills.
At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics.
See all J-1 Visa AI Platform Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new J-1 Visa AI Platform Engineer Jobs.
Get Access To All JobsTips for Finding J-1 Visa Sponsorship as an AI Platform Engineer
Align your credentials with specialty occupation standards
J-1 visa Trainee and Research Scholar categories require documented evidence that your background matches the technical scope of the role. Compile your degree transcripts, publications, and prior AI or MLOps project portfolios before approaching host employers.
Verify host employers' prior J-1 hosting history
Search Migrate Mate to identify U.S. companies that have hosted J-1 exchange visitors in engineering and AI roles. Hosts with prior experience know the training plan requirements and are far less likely to withdraw offers mid-process.
Distinguish Trainee from Research Scholar before applying
If you hold a degree and have under five years of post-graduation experience in AI infrastructure, Trainee is the applicable category. Research Scholar applies to university-affiliated or postdoctoral work. Targeting the wrong category delays your DS-2019 issuance.
Build a specific training plan for AI platform work
Your designated sponsor requires a detailed Training or Internship Placement Plan, form DS-7002, before issuing the DS-2019. Document the specific skills you'll develop, such as model deployment pipelines, infrastructure orchestration, or LLM evaluation frameworks, mapped to monthly milestones.
Check your role for the two-year home residency requirement
If your J-1 funding comes from your home government or a U.S. government program, or if your country of nationality appears on the USCIS Skills List, a two-year home residency requirement applies before you can change to most other U.S. visa statuses.
Confirm prevailing wage compliance before accepting an offer
Your host employer must pay at least the prevailing wage for the role's location and SOC code. Use the OFLC Wage Search to verify the applicable wage level for AI Platform Engineer positions in your target metro area before signing any offer letter.
AI Platform Engineer J-1 Visa: Frequently Asked Questions
Which J-1 program category fits an AI Platform Engineer role?
The Trainee category applies to most AI Platform Engineer candidates who have a degree in computer science, engineering, or a related field and fewer than five years of relevant post-graduation experience. The Research Scholar category fits candidates pursuing AI infrastructure research at a U.S. university or national laboratory. The Intern category covers current students completing a degree program who take on a structured AI engineering placement during or immediately after their studies.
Who actually sponsors the J-1 visa, and what does the host employer do?
The J-1 visa sponsor is a U.S. Department of State-designated organization, such as IIE, Cultural Vistas, or AIPT, that issues your DS-2019 form and monitors your program compliance. The tech company or research institution where you work is your host employer, not your visa sponsor. Your host signs the DS-7002 training plan and provides the technical experience, but the designated sponsor holds legal responsibility for your exchange program.
How do I find U.S. employers willing to host J-1 AI platform engineers?
Use Migrate Mate to search for AI Platform Engineer roles at U.S. employers that have prior experience hosting international exchange visitors. Filtering for J-1-aligned roles saves significant time because many employers, even large tech companies, are unfamiliar with the host organization obligations and will decline without an established internal process for managing exchange visitor compliance.
Does the two-year home residency requirement affect AI Platform Engineers?
It can. If your J-1 program is funded by your home-country government, a U.S. government agency, or if your home country and specialty appear on the USCIS Skills List, you'll be subject to the two-year home residency requirement under INA section 212(e). This means you must return to your home country for two years before applying for an H-1B visa, L-1 visa, or immigrant visa. A waiver is available through USCIS under specific circumstances, but it adds time and complexity to any future status change.
Can I extend my J-1 Trainee status if my AI platform project runs longer than planned?
The J-1 Trainee category has a maximum duration of 18 months, with a limited extension available up to 18 additional months for trainees in fields that USCIS recognizes as requiring longer skill development. Extensions require your designated sponsor's approval and an updated DS-7002. You cannot extend beyond the regulatory maximum, and time spent in a prior J-1 program in the same field counts against your total. Plan your project milestones and exit timeline accordingly from the start.