AI Engineer Jobs at NVIDIA with Visa Sponsorship
NVIDIA hires AI Engineers across research, infrastructure, and applied teams, with roles spanning model development, training optimization, and deployment at scale. The company has a consistent track record of sponsoring work visas for this function, making it a realistic target for international candidates with the right technical background.
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Get Access To All JobsNVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Make the choice, join our diverse team today!
Working at the Silicon Co-design Engineering Team at NVIDIA, you will be responsible for productizing NVIDIA's chips into groundbreaking consumer, professional, server, mobile, and automotive solutions. The qualified candidate should be comfortable in a lab environment and should demonstrate a passion towards creation, execution and improvement of silicon validation plans.
What you’ll be doing:
- Build and deploy AI/ML + GenAI solutions (LLMs, classical ML) to accelerate silicon co-design and validation workflows.
- Develop AI assistants and agentic systems for SCG engineers using RAG, tool-calling, and fine-tuned models.
- Create scalable data + MLOps pipelines to collect/curate chip design & validation data and support training, evaluation, and production deployment.
- Partner with cross-functional silicon teams to identify high-impact automation opportunities, integrate solutions into existing flows, and drive measurable improvements in turnaround time and quality.
- Prototype and apply modern ML techniques relevant to silicon co-design and share learnings via tech talks/knowledge sharing.
What we need to see:
- M.S. or Ph.D. (or completing within 6 months) in CS/EE/CE or related field or equivalent experience.
- Programming: Strong Python; plus C/C++ and/or Tcl/Perl/Bash.
- ML Foundation: Understanding of model development and evaluation; familiarity with Transformers/LLMs and at least one of CNN/RNN/GNN concepts.
- Frameworks: Hands-on with ML framework PyTorch / TensorFlow.
- Software Engineering: Strong fundamentals in Git, code reviews, testing, CI/CD, documentation.
- Skills: Strong debugging/problem-solving, ability to handle ambiguity, and effective communication/collaboration across HW/SW teams.
- Motivation: Interest in applying AI to semiconductor co-design/validation problems and learning the domain quickly.
Ways to stand out from the crowd:
- Familiarity with statistical methods, tools for data analysis, and analyzing large datasets to draw actionable conclusions, possibly applying deep learning techniques.
- Knowledgeable in signal integrity, timing analysis, fault analysis, sampling, computer architecture, filters.
- Familiar with lab tools (oscilloscopes and logic analyzers).
- Experience in Database and Web Development is a plus!
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We welcome you join our team with some of the most hard-working people in the world working together to promote rapid growth. Are you passionate about becoming a part of a best-in-class team supporting the latest in GPU and AI technology? If so, 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 100,000 USD - 166,750 USD for Level 1, and 116,000 USD - 189,750 USD for Level 2.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 27, 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.
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Make the choice, join our diverse team today!
Working at the Silicon Co-design Engineering Team at NVIDIA, you will be responsible for productizing NVIDIA's chips into groundbreaking consumer, professional, server, mobile, and automotive solutions. The qualified candidate should be comfortable in a lab environment and should demonstrate a passion towards creation, execution and improvement of silicon validation plans.
What you’ll be doing:
- Build and deploy AI/ML + GenAI solutions (LLMs, classical ML) to accelerate silicon co-design and validation workflows.
- Develop AI assistants and agentic systems for SCG engineers using RAG, tool-calling, and fine-tuned models.
- Create scalable data + MLOps pipelines to collect/curate chip design & validation data and support training, evaluation, and production deployment.
- Partner with cross-functional silicon teams to identify high-impact automation opportunities, integrate solutions into existing flows, and drive measurable improvements in turnaround time and quality.
- Prototype and apply modern ML techniques relevant to silicon co-design and share learnings via tech talks/knowledge sharing.
What we need to see:
- M.S. or Ph.D. (or completing within 6 months) in CS/EE/CE or related field or equivalent experience.
- Programming: Strong Python; plus C/C++ and/or Tcl/Perl/Bash.
- ML Foundation: Understanding of model development and evaluation; familiarity with Transformers/LLMs and at least one of CNN/RNN/GNN concepts.
- Frameworks: Hands-on with ML framework PyTorch / TensorFlow.
- Software Engineering: Strong fundamentals in Git, code reviews, testing, CI/CD, documentation.
- Skills: Strong debugging/problem-solving, ability to handle ambiguity, and effective communication/collaboration across HW/SW teams.
- Motivation: Interest in applying AI to semiconductor co-design/validation problems and learning the domain quickly.
Ways to stand out from the crowd:
- Familiarity with statistical methods, tools for data analysis, and analyzing large datasets to draw actionable conclusions, possibly applying deep learning techniques.
- Knowledgeable in signal integrity, timing analysis, fault analysis, sampling, computer architecture, filters.
- Familiar with lab tools (oscilloscopes and logic analyzers).
- Experience in Database and Web Development is a plus!
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We welcome you join our team with some of the most hard-working people in the world working together to promote rapid growth. Are you passionate about becoming a part of a best-in-class team supporting the latest in GPU and AI technology? If so, 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 100,000 USD - 166,750 USD for Level 1, and 116,000 USD - 189,750 USD for Level 2.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 27, 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 101+ AI Engineer at NVIDIA jobs
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Get Access To All JobsTips for Finding AI Engineer Jobs at NVIDIA Jobs
Align your portfolio to NVIDIA's AI stack
NVIDIA's AI Engineer roles emphasize CUDA, TensorRT, and large-scale model training on GPU clusters. Build and document projects that use these tools directly. A portfolio showing hands-on NVIDIA infrastructure work signals fit before your resume does.
Target roles that clear the specialty occupation bar
For H-1B eligibility, your role needs to require a specific bachelor's degree field. AI Engineer positions tied to machine learning research or inference optimization have a cleaner specialty occupation case than generalist software roles. Review the job description language before applying.
Get your credentials evaluated before NVIDIA's offer stage
NVIDIA's recruiting moves fast. If your degree is from a non-U.S. institution, have a NACES-accredited evaluator assess its equivalency to a U.S. bachelor's in computer science or a related field before you receive an offer, not after.
Ask about E-3 eligibility if you hold Australian citizenship
Australian citizens can use the E-3 visa for specialty occupation roles at NVIDIA. It has no lottery and allows two-year renewable terms. If your recruiter defaults to H-1B, flag your citizenship and ask whether the E-3 path is available for your role.
Use Migrate Mate to find open AI Engineer roles at NVIDIA
Identifying which of NVIDIA's current AI Engineer postings are open to sponsored candidates saves time during a time-sensitive search. Migrate Mate filters NVIDIA roles specifically by visa type so you can focus your applications on positions where sponsorship is confirmed.
Confirm LCA filing timing with your NVIDIA HR contact
NVIDIA's HR team files your Labor Condition Application with the DOL before USCIS receives the H-1B petition. If your start date is firm, verify that the LCA was submitted and certified at least a week before your I-129 is filed to avoid processing gaps.
AI Engineer at NVIDIA jobs are hiring across the US. Find yours.
Find AI Engineer at NVIDIA JobsFrequently Asked Questions
Does NVIDIA sponsor H-1B visas for AI Engineers?
Yes. NVIDIA sponsors H-1B visas for AI Engineer roles, and the company has a consistent pattern of doing so across research, applied, and infrastructure teams. Because H-1B is subject to an annual cap and lottery, timing matters. NVIDIA typically initiates sponsorship discussions during or after the offer stage, and your start date will depend on lottery selection and USCIS processing timelines.
How do I apply for AI Engineer jobs at NVIDIA?
Applications go through NVIDIA's careers portal at nvidia.com/en-us/about-nvidia/careers. Search by role title and filter for AI or machine learning positions. If you want to narrow results to roles with confirmed visa sponsorship, Migrate Mate aggregates NVIDIA's open AI Engineer positions by visa type, which saves time if you're on a deadline like OPT expiration or a 60-day grace period.
Which visa types does NVIDIA commonly use for AI Engineer roles?
NVIDIA sponsors H-1B and E-3 visas for nonimmigrant work authorization, and supports EB-2 and EB-3 Green Card pathways for longer-term permanent residence. E-3 is available exclusively to Australian citizens and skips the H-1B lottery entirely. The right visa depends on your nationality, your degree, and whether the role meets specialty occupation requirements under USCIS guidelines.
What qualifications does NVIDIA expect for AI Engineer roles?
Most AI Engineer postings at NVIDIA specify a bachelor's or master's degree in computer science, electrical engineering, or a closely related field. Hands-on experience with GPU-accelerated computing, deep learning frameworks like PyTorch, and model optimization tools such as TensorRT is expected. Research-oriented roles often require a publication record or demonstrated experience with large-scale model training at the infrastructure level.
How do I time my application if my work authorization is expiring soon?
If you're on OPT or in a 60-day grace period, apply early and flag your authorization timeline to your NVIDIA recruiter at the point of offer. H-1B cap filings open in March for October 1 starts, so if you miss that window, NVIDIA may be able to use cap-exempt options or bridge your status depending on your circumstances. E-3 applicants have more flexibility since there's no lottery and consular appointments can move faster.
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