TN Visa AI Research Engineer Jobs
AI Research Engineer roles qualify for TN visa sponsorship under the USMCA's Computer Systems Analyst category when the position centers on developing or evaluating AI systems using theoretical and applied computer science. Canadian citizens can enter at the border without a cap or lottery. Mexican citizens require a consulate appointment.
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INTRODUCTION
NVIDIA's GPUs are at the core of modern AI infrastructure, from training large-scale models to running inference in production. That position depends on software as much as hardware, and compiler engineering is a big part of what makes it work.
We are looking for outstanding AI Research Engineer /Applied Scientist focused on Compilers /Low-level optimization to join the team and develop groundbreaking technologies in machine learning compilers and AI systems. We build innovative AI compiler solutions that work together with NVIDIA's software stack to provide comprehensive acceleration for modern machine learning models.
ROLE AND RESPONSIBILITIES:
- Help trailblaze company efforts in applying AI within conventional compilation pipelines.
- Design and implement AI-based technology addressing core problems of low-level GPU programming.
- Build training pipelines for supervised fine-tuning and reinforcement learning (RL/RLHF-style or policy optimization variants).
- Define model inputs/outputs over compiler low level compiler representations.
- Develop evaluation frameworks to measure code quality, runtime, compile-time overhead, and correctness.
- Intelligent (domain task based) prompt engineering.
- Collaborate with compiler engineers to integrate learned policies into production toolchains.
- Prototype and iterate on model architectures, prompts, and fine-tuning strategies for scheduling and allocation tasks.
- Create datasets from compiler traces, optimization passes, and target-specific performance signals.
- Apply RL techniques to optimize for downstream objectives (performance, spill reduction, instruction-level parallelism, etc.) and run rigorous experiments, ablations, and benchmarking across workloads and hardware targets.
BASIC QUALIFICATIONS:
- M.S./PhD degree in Computer Engineering, Computer Science related technical field (or equivalent experience).
- 5+ years of experience building AI/ML systems.
- Strong software engineering skills in Python and at least one systems language (C++ preferred).
- Hands-on experience training/fine-tuning large models (Transformers, PEFT/LoRA, distributed training).
- Solid understanding of machine learning fundamentals and experimentation best practices.
- Experience with reinforcement learning (e.g., policy gradients, actor-critic, offline RL, bandit-style optimization).
- Knowledge of prompt-engineering techniques.
- Ability to work across research and engineering, from prototype to production.
PREFERRED QUALIFICATIONS:
- Distributed training/inference at scale.
- Experience working with the NVIDIA NeMo framework.
- Understanding of GPU performance, experience with benchmarking suites and performance profiling tools.
- Formal methods or static analysis familiarity for correctness guarantees.
- CUDA programming experience.
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous program manager with a real passion for technology, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 26, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

INTRODUCTION
NVIDIA's GPUs are at the core of modern AI infrastructure, from training large-scale models to running inference in production. That position depends on software as much as hardware, and compiler engineering is a big part of what makes it work.
We are looking for outstanding AI Research Engineer /Applied Scientist focused on Compilers /Low-level optimization to join the team and develop groundbreaking technologies in machine learning compilers and AI systems. We build innovative AI compiler solutions that work together with NVIDIA's software stack to provide comprehensive acceleration for modern machine learning models.
ROLE AND RESPONSIBILITIES:
- Help trailblaze company efforts in applying AI within conventional compilation pipelines.
- Design and implement AI-based technology addressing core problems of low-level GPU programming.
- Build training pipelines for supervised fine-tuning and reinforcement learning (RL/RLHF-style or policy optimization variants).
- Define model inputs/outputs over compiler low level compiler representations.
- Develop evaluation frameworks to measure code quality, runtime, compile-time overhead, and correctness.
- Intelligent (domain task based) prompt engineering.
- Collaborate with compiler engineers to integrate learned policies into production toolchains.
- Prototype and iterate on model architectures, prompts, and fine-tuning strategies for scheduling and allocation tasks.
- Create datasets from compiler traces, optimization passes, and target-specific performance signals.
- Apply RL techniques to optimize for downstream objectives (performance, spill reduction, instruction-level parallelism, etc.) and run rigorous experiments, ablations, and benchmarking across workloads and hardware targets.
BASIC QUALIFICATIONS:
- M.S./PhD degree in Computer Engineering, Computer Science related technical field (or equivalent experience).
- 5+ years of experience building AI/ML systems.
- Strong software engineering skills in Python and at least one systems language (C++ preferred).
- Hands-on experience training/fine-tuning large models (Transformers, PEFT/LoRA, distributed training).
- Solid understanding of machine learning fundamentals and experimentation best practices.
- Experience with reinforcement learning (e.g., policy gradients, actor-critic, offline RL, bandit-style optimization).
- Knowledge of prompt-engineering techniques.
- Ability to work across research and engineering, from prototype to production.
PREFERRED QUALIFICATIONS:
- Distributed training/inference at scale.
- Experience working with the NVIDIA NeMo framework.
- Understanding of GPU performance, experience with benchmarking suites and performance profiling tools.
- Formal methods or static analysis familiarity for correctness guarantees.
- CUDA programming experience.
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous program manager with a real passion for technology, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 26, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
See all 509+ AI Research Engineer jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Research Engineer roles.
Get Access To All JobsTips for Finding TN Visa Sponsorship as an AI Research Engineer
Frame your credentials around CS theory
TN approval for AI Research Engineer roles hinges on demonstrating a computer science or engineering degree, not just machine learning experience. Pull your transcripts and confirm your degree title maps directly to a theoretical or applied CS discipline before applying.
Target employers with dedicated research labs
Companies running formal AI research divisions already understand the TN Computer Systems Analyst category. Focus your search on organizations that publish peer-reviewed work, since their HR and legal teams have navigated this classification before.
Ask employers to define the role in your offer letter
CBP officers evaluate TN petitions at the border, not USCIS. Your offer letter must describe duties in terms of systems analysis and AI model design, not vague engineering tasks. A poorly worded letter is the most common reason TN applications are delayed at the port of entry.
Use Migrate Mate to surface active TN sponsors
Searching for roles at employers with recent visa filings saves weeks of outreach. Migrate Mate filters AI Research Engineer listings by employer sponsorship experience, so you're contacting companies who have already demonstrated expertise with work visa processes.
Prepare for Mexican nationals' consulate timeline
Mexican citizens cannot self-adjudicate at the border and must schedule a consulate appointment, which can take several weeks. Build at least 60 days into your job search timeline between an accepted offer and your intended U.S. start date.
Align your research publications with the specialty occupation
CBP and consular officers respond well to evidence of formal AI research output. A list of published papers, conference proceedings, or technical reports filed with your TN package strengthens the argument that the role requires your specific theoretical expertise.
AI Research Engineer jobs are hiring across the US. Find yours.
Find AI Research Engineer JobsAI Research Engineer TN Visa: Frequently Asked Questions
Does an AI Research Engineer role qualify for a TN visa?
Yes, provided the role is structured around computer systems analysis and AI model development grounded in theoretical computer science. TN classification requires a direct connection between your degree field and the job duties. Roles focused purely on deploying pre-built models without a research or analysis component are harder to support under the Computer Systems Analyst category.
How does TN visa sponsorship compare to H-1B for AI Research Engineers?
TN has no annual lottery, no filing cap for Canadians, and no USCIS petition queue, so qualified Canadian professionals can start work far faster than under H-1B. The tradeoff is that TN status doesn't lead to a green card on its own and must be renewed indefinitely. H-1B offers dual intent and a path to permanent residence, which matters if long-term U.S. settlement is your goal.
Can I switch AI Research Engineer employers while on TN status?
Yes, but you need a new TN approval before starting with the new employer. TN status is employer-specific. Canadian citizens can obtain a new TN at the border with a fresh offer letter and supporting documents. Mexican citizens must return to a U.S. consulate. There is no portability provision under TN the way AC21 allows for H-1B holders.
Where can I find AI Research Engineer jobs with confirmed TN visa sponsorship?
Migrate Mate is built specifically for Canadian and Mexican professionals searching for U.S. roles that may qualify for TN visa sponsorship. The platform surfaces AI Research Engineer listings from employers with recent visa filings, which removes the guesswork of cold-contacting companies that may not have experience with work visa sponsorship.
What documents does my employer need to provide for TN sponsorship?
Your employer must produce a detailed offer letter specifying your job title, duties, the TN category being claimed, your degree requirement, and your anticipated length of employment. For Canadian citizens, this letter is presented directly to CBP at the port of entry. For Mexican nationals, it accompanies the DS-160 and supporting materials submitted to the U.S. consulate.
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