AI Product Engineer Jobs at NVIDIA with Visa Sponsorship
AI Product Engineer jobs at NVIDIA sit at the intersection of applied research and product development, requiring deep technical fluency in AI systems and the ability to ship at scale. NVIDIA has a consistent track record of sponsoring work visas for engineers in this function, including H-1B visa and E-3 visa pathways.
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INTRODUCTION
At Nvidia we meet customers where they are on their AI journey on our GPUs - this means we build best in class frameworks in OSS and support a robust eco system of other OSS frameworks. As a Product Manager for AI Platform training you will be responsible for building the tools, SDKs, and libraries which enable model builders to get the best large scale performance, resilience and experience on NVIDIA GPUs. As NVIDIA Product Managers, our goal is to enable researchers and operators to be successful on the NVIDIA Platform, and push the boundaries of what is possible in their research and research-to-production! As Product Managers, we are the champions inside NVIDIA for frontier model builders looking to push the bounds of scale and resilience for current and emerging modeling paradigms on GPUs. We work directly with customers inside and outside of the company to identify key improvements, create roadmaps, and stay alert on the training/post training landscape. We also work with NVIDIA leaders to define clear product strategy, and marketing team teams to build go-to-market plans. The Product Management organization at NVIDIA is a small, strong, and impactful group. We focus on enabling deep learning across all GPU use cases and providing great products for our users. We are seeking a rare blend of product skills, technical depth, and passion to make NVIDIA great. Does that sound familiar? If so, we would love to hear from you!
ROLE AND RESPONSIBILITIES
What You'll Be Doing
- Create products to help researchers and production model builders
- Develop product strategy, roadmaps, and go-to-market plans
- Collaborate with internal and external customers to build product-based roadmaps for training/post training software
- Work with leadership to align with and drive company strategy
BASIC QUALIFICATIONS
What We Need To See
- Experience with training/post training and optimization software (ex. PyTorch distributed, torchtitan, VeRL, Nemo Framework, etc.)
- Demonstrable knowledge of GenAI or machine learning concepts, particularly around model training, performance optimization, and software development and delivery
- Experience with large scale distributed systems
- BS or MS degree in Computer Science, Computer Engineering, or similar experience (or equivalent experience)
- 15+ years of technical product management, or similar, experience at a technology company
- Strong communication and interpersonal skills
PREFERRED QUALIFICATIONS
Ways To Stand Out From The Crowd
- Experience leading GenAI/RecSys research to production at scale
- Working on Open Source & Github-first developer products with deep customer interactions
- Knowledge of GPU architecture, HW/SW co-design, and performance profiling
COMPENSATION
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 240,000 USD - 379,500 USD. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until January 13, 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.
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Get Access To All JobsTips for Finding AI Product Engineer Jobs at NVIDIA
Frame Your Portfolio Around Deployed AI Systems
NVIDIA evaluates AI Product Engineers on shipped work, not research abstracts. Prepare a portfolio showing production-level AI systems you've built, with clear ownership over architecture decisions, model integration, and performance outcomes at scale.
Target NVIDIA's Platform and Developer Products Teams
NVIDIA's AI Product Engineer openings cluster around platforms like CUDA, TensorRT, and NIM. Aligning your application to these product lines signals product-domain fit, which hiring managers weigh heavily against general AI experience.
Verify E-3 Eligibility Before Accepting an Offer
If you're an Australian citizen, NVIDIA sponsors E-3 visas for this function. Confirm that your role will be classified as a specialty occupation before signing anything. Your degree field must directly align with the AI Product Engineer job description to satisfy DOL requirements.
Clarify Sponsorship Scope During Offer Negotiation
Ask NVIDIA's recruiter explicitly whether the offer includes both H-1B filing and Green Card sponsorship through EB-2 or EB-3 PERM. Large employers sometimes separate these commitments, and getting clarity upfront prevents delays after you've started.
Use Migrate Mate to Find Verified AI Product Engineer Openings at NVIDIA
Not every NVIDIA job listing signals genuine sponsorship availability. Use Migrate Mate to browse AI Product Engineer roles at NVIDIA that are verified for visa sponsorship, so you're applying where the pathway is confirmed rather than inferred.
Time H-1B Applications Around NVIDIA's Hiring Cycles
NVIDIA ramps AI Product Engineer hiring in Q4 and Q1. If you're on OPT, coordinate your offer timing so USCIS receives your H-1B petition before the April 1 cap-subject filing window. Missing it means waiting 12 months for the next lottery cycle.
Frequently Asked Questions
Does NVIDIA sponsor H-1B visas for AI Product Engineers?
Yes, NVIDIA sponsors H-1B visas for AI Product Engineer roles. NVIDIA has sponsored H-1B petitions for engineers in this function across multiple fiscal years, making it one of the more accessible paths for international candidates. Your role must qualify as a specialty occupation under USCIS standards, which for AI Product Engineers typically requires a bachelor's degree or higher in computer science, electrical engineering, or a closely related technical field.
How do I apply for AI Product Engineer jobs at NVIDIA?
Apply directly through NVIDIA's careers site or use Migrate Mate to browse verified AI Product Engineer openings with confirmed visa sponsorship. Tailor your resume to reflect production AI system experience, particularly with NVIDIA's product ecosystem. Expect a technical screen, a system design round focused on AI infrastructure, and a product-sense interview. Indicating visa sponsorship needs early in the recruiter screen avoids mismatched expectations later in the process.
Which visa types does NVIDIA commonly use for AI Product Engineers?
NVIDIA sponsors H-1B visas for most international AI Product Engineers and E-3 visas specifically for Australian citizens. For longer-term permanent residency, NVIDIA also sponsors EB-2 and EB-3 Green Cards through the PERM labor certification process. The right pathway depends on your nationality, degree field, and where you are in your career. Australian applicants should evaluate the E-3 first given its simpler process and no lottery requirement.
What qualifications does NVIDIA expect for AI Product Engineer roles?
NVIDIA's AI Product Engineer roles typically require a bachelor's or master's degree in computer science, machine learning, or a related engineering discipline, along with hands-on experience building and deploying AI models in production environments. Familiarity with NVIDIA's software stack, including CUDA, TensorRT, or Triton, is a strong differentiator. Candidates who can bridge the gap between model research and scalable product integration are prioritized over those with purely academic AI backgrounds.
How do I plan my visa timeline when joining NVIDIA as an AI Product Engineer?
If you're transitioning from OPT, your start date needs to align with USCIS H-1B cap filing, which opens April 1 for an October 1 start. NVIDIA's legal team handles the I-129 filing, but you're responsible for coordinating your OPT expiration and STEM OPT extension if needed. E-3 applicants have more flexibility since there's no lottery, but still need a certified Labor Condition Application from DOL before attending a consular interview.