J-1 Visa Software Engineer AI Jobs
Software Engineer AI roles in the United States are available to international candidates through J-1 visa sponsorship under the Trainee or Research Scholar program category, depending on your career stage. Designated sponsor organizations issue your DS-2019 once a U.S. host employer commits to a structured training plan aligned with your AI specialization.
See All Software Engineer AI JobsOverview
Showing 5 of 106+ Software Engineer AI jobs
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all 106+ Software Engineer AI jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Software Engineer AI roles.
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:
-
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.
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 106+ Software Engineer AI jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Software Engineer AI roles.
Get Access To All JobsTips for Finding J-1 Visa Sponsorship in Software Engineer AI
Align your CV to DS-2019 training objectives
Designated sponsors require a detailed training plan before issuing your DS-2019. Structure your CV around specific AI competencies like model fine-tuning or MLOps pipelines so host employers can map your background directly to J-1 training objectives.
Distinguish Trainee from Research Scholar eligibility
J-1 Trainee status fits early-career AI engineers with a degree and under five years of experience. If your role involves original AI research at a university or research institute, Research Scholar is the correct category and carries different duration limits.
Search Migrate Mate for J-1-aligned AI roles
Use Migrate Mate to filter for U.S. employers actively hosting J-1 exchange visitors in software and AI functions. Targeting companies with an existing J-1 host relationship shortens the sponsorship timeline considerably.
Verify your host employer's E-Verify enrollment early
Your designated sponsor will confirm whether your host employer participates in E-Verify before approving your training plan. Raise this with the hiring team during the offer stage, not after you have accepted, to avoid delays in DS-2019 issuance.
Check prevailing wage compliance using OFLC Wage Search
Designated sponsors validate that your host employer's offered compensation meets DOL prevailing wage levels for your AI role and location. Run the OFLC Wage Search for your SOC code before negotiating your offer so you enter discussions with accurate benchmarks.
Plan for the two-year home residency requirement
AI engineers sponsored under Research Scholar or Specialist categories often carry the two-year home residency requirement, which affects later H-1B or green card eligibility. Confirm with your designated sponsor whether your specific funding source or nationality triggers this requirement before signing.
Software Engineer AI jobs are hiring across the US. Find yours.
Find Software Engineer AI JobsSoftware Engineer AI J-1 Visa: Frequently Asked Questions
Which J-1 program category fits a Software Engineer AI role?
Most AI software engineers enter on J-1 Trainee status, which suits candidates who hold a degree in computer science, data science, or a related field and have fewer than five years of post-degree experience. Engineers conducting original AI research embedded within a university or accredited research institution may qualify instead under the Research Scholar category, which allows longer program durations and covers a different scope of activities.
Who actually sponsors the J-1 visa for an AI engineering role?
The visa sponsor is a U.S. Department of State-designated sponsor organization such as CIEE, Cultural Vistas, or AIPT, not the tech company hiring you. That company is your host employer. The designated sponsor issues your DS-2019, reviews your training plan, and monitors compliance throughout your program. Your employer cannot sponsor the J-1 directly the way it would an H-1B petition.
How do I find U.S. employers willing to host J-1 AI engineers?
Search Migrate Mate to identify U.S. companies that have hosted J-1 exchange visitors in technical roles. Employers already familiar with J-1 host requirements move faster because they understand training plan documentation and designated sponsor coordination. Cold outreach to companies with no J-1 history significantly lengthens the process.
Does the two-year home residency requirement affect AI engineers on J-1 visas?
It can, and for AI engineers it is one of the most consequential details to clarify before accepting an offer. The requirement applies when your J-1 program is funded by your home government, a U.S. government agency, or when your home country designates your skill set as in shortage. If triggered, you must return home for two years before changing to H-1B or applying for a green card, unless you obtain a waiver.
What does the J-1 training plan need to include for an AI engineering placement?
Your designated sponsor requires a detailed Training or Internship Placement Plan, called a DS-7002, that maps each phase of your program to specific AI competencies such as data pipeline development, model evaluation, or deployment engineering. The plan must show observable skill progression and cannot describe routine production work. Your host employer drafts this document, but the designated sponsor must approve it before your DS-2019 is issued.
See which Software Engineer AI employers are hiring and sponsoring visas right now.
Search Software Engineer AI Jobs