AI ML Engineering Jobs at NVIDIA with Visa Sponsorship
AI ML Engineering jobs at NVIDIA sit at the intersection of GPU architecture, large-scale model training, and production inference systems. NVIDIA has a strong track record of sponsoring international engineers across H-1B visa, E-3 visa, and employment-based Green Card pathways, making it a viable target for visa-dependent candidates with deep ML expertise.
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Get Access To All JobsINTRODUCTION
NVIDIA is building the world’s leading AI company, and we are looking for an experienced Cloud Solution Architect to help assist customers with adoption of GPU hardware and Software, as well as building and deploying Machine Learning (ML), Deep Learning (DL), data analytics solutions on various Cloud Computing Platforms. As part of the Solutions Architecture team, we work with some of the most exciting computing hardware and software technologies including the latest breakthroughs in machine learning and data science. A Solutions Architect is the first line of technical expertise between NVIDIA and our customers so you will engage directly with developers, researchers, and data scientists with some of NVIDIA’s most strategic technology customers as well as work directly with business and engineering teams on product strategy. We are looking for a Solutions Architect to help drive end-to-end technology solutions applying NVIDIA’s full set of technologies based on business needs of customers. Join us in this exciting endeavor!
ROLE AND RESPONSIBILITIES
What You Will Be Doing
- Working with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s ML/DL and data science software and hardware technologies
- Build and deploy AI/ML solutions at scale using NVIDIA's AI software on cloud-based GPU platforms.
- Build custom PoCs for solution that address customer’s critical business needs applying NVIDIA hardware and software technology
- Partner with Sales Account Managers or Developer Relations Managers to identify and secure new business opportunities for NVIDIA products and solutions for ML/DL and other software solutions
- Prepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc.
- Conduct regular technical customer meetings for project/product roadmap, feature discussions, and intro to new technologies. Establish close technical ties to the customer to facilitate rapid resolution of customer issues
BASIC QUALIFICATIONS
What We Need To See
- 3+ years of Solutions Engineering (or similar Sales Engineering roles) or equivalent experience
- 3+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow or PyTorch, GPU, and CUDA experience extremely helpful.
- BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or other Engineering fields or equivalent experience.
- Established track record of deploying solutions in cloud computing environments including AWS, GCP, or Azure
- Knowledge of DevOps/ML Ops technologies such as Docker/containers, Kubernetes, data center deployments
- Ability to use at least one scripting language (i.e., Python)
- Good programming and debugging skills
- Ability to communicate your ideas/code clearly through documents, presentation etc.
PREFERRED QUALIFICATIONS
Ways To Stand Out From The Crowd
- AWS, GCP or Azure Professional Solution Architect Certification.
- Hands-on experience with NVIDIA GPUs and SDKs (e.g. CUDA, RAPIDS, Triton etc.)
- System-level experience specifically GPU-based systems
- Experience with Deep Learning at scale
- Familiarity with parallel programming and distributed computing platforms
We make extensive use of conferencing tools, but occasional travel is required for local on-site visit to customers and industry events. NVIDIA is 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. If you're creative and autonomous, we want to hear from you!
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 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until March 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.
JR2000691
INTRODUCTION
NVIDIA is building the world’s leading AI company, and we are looking for an experienced Cloud Solution Architect to help assist customers with adoption of GPU hardware and Software, as well as building and deploying Machine Learning (ML), Deep Learning (DL), data analytics solutions on various Cloud Computing Platforms. As part of the Solutions Architecture team, we work with some of the most exciting computing hardware and software technologies including the latest breakthroughs in machine learning and data science. A Solutions Architect is the first line of technical expertise between NVIDIA and our customers so you will engage directly with developers, researchers, and data scientists with some of NVIDIA’s most strategic technology customers as well as work directly with business and engineering teams on product strategy. We are looking for a Solutions Architect to help drive end-to-end technology solutions applying NVIDIA’s full set of technologies based on business needs of customers. Join us in this exciting endeavor!
ROLE AND RESPONSIBILITIES
What You Will Be Doing
- Working with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s ML/DL and data science software and hardware technologies
- Build and deploy AI/ML solutions at scale using NVIDIA's AI software on cloud-based GPU platforms.
- Build custom PoCs for solution that address customer’s critical business needs applying NVIDIA hardware and software technology
- Partner with Sales Account Managers or Developer Relations Managers to identify and secure new business opportunities for NVIDIA products and solutions for ML/DL and other software solutions
- Prepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc.
- Conduct regular technical customer meetings for project/product roadmap, feature discussions, and intro to new technologies. Establish close technical ties to the customer to facilitate rapid resolution of customer issues
BASIC QUALIFICATIONS
What We Need To See
- 3+ years of Solutions Engineering (or similar Sales Engineering roles) or equivalent experience
- 3+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow or PyTorch, GPU, and CUDA experience extremely helpful.
- BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or other Engineering fields or equivalent experience.
- Established track record of deploying solutions in cloud computing environments including AWS, GCP, or Azure
- Knowledge of DevOps/ML Ops technologies such as Docker/containers, Kubernetes, data center deployments
- Ability to use at least one scripting language (i.e., Python)
- Good programming and debugging skills
- Ability to communicate your ideas/code clearly through documents, presentation etc.
PREFERRED QUALIFICATIONS
Ways To Stand Out From The Crowd
- AWS, GCP or Azure Professional Solution Architect Certification.
- Hands-on experience with NVIDIA GPUs and SDKs (e.g. CUDA, RAPIDS, Triton etc.)
- System-level experience specifically GPU-based systems
- Experience with Deep Learning at scale
- Familiarity with parallel programming and distributed computing platforms
We make extensive use of conferencing tools, but occasional travel is required for local on-site visit to customers and industry events. NVIDIA is 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. If you're creative and autonomous, we want to hear from you!
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 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until March 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.
JR2000691
See all AI ML Engineering Jobs at NVIDIA
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI ML Engineering Jobs at NVIDIA.
Get Access To All JobsTips for Finding AI ML Engineering Jobs at NVIDIA
Tailor your portfolio to NVIDIA's stack
NVIDIA's AI ML Engineering roles consistently require hands-on experience with CUDA, TensorRT, and distributed training frameworks. Document projects involving GPU optimization or large model inference before applying, not after you land an interview.
Target teams building production AI systems
NVIDIA hires ML engineers into distinct verticals: autonomous vehicles, cloud AI, and developer tools. Applying to a team whose product aligns with your domain significantly improves your chances of clearing the technical screen.
Confirm your visa type before the offer stage
NVIDIA sponsors both H-1B and E-3 visas for this role. If you're an Australian citizen, raising the E-3 pathway early avoids delays, since E-3 doesn't require lottery selection and can be processed on a faster timeline.
Prepare for the specialty occupation standard early
USCIS requires H-1B petitions to demonstrate the role qualifies as a specialty occupation. For AI ML Engineering, that means your degree field and job duties need to align precisely. Gather transcripts and any graduate research documentation before your employer files.
Understand NVIDIA's internal immigration timeline
Large technology employers typically begin H-1B cap-subject filings in March for an October start date. If you're interviewing in Q4 or Q1, factor this window into your offer negotiation so your start date aligns with USCIS processing.
Use Migrate Mate to filter open roles by visa type
NVIDIA posts AI ML Engineering positions across multiple teams simultaneously. Use Migrate Mate to filter live openings specifically by visa sponsorship type, so you apply to roles where your visa category is already confirmed as supported.
Frequently Asked Questions
Does NVIDIA sponsor H-1B visas for AI ML Engineers?
Yes, NVIDIA sponsors H-1B visas for AI ML Engineering roles. For cap-subject candidates, NVIDIA files petitions in the annual H-1B lottery window, which opens in March. If you're already in H-1B status with another employer, NVIDIA can file a transfer petition outside the lottery, which avoids the wait.
Which visa types does NVIDIA sponsor for AI ML Engineering roles?
NVIDIA sponsors H-1B visas for most international candidates in AI ML Engineering. Australian citizens can pursue the E-3 visa instead, which has no annual lottery and is generally faster to obtain. For candidates on a longer-term path, NVIDIA also supports EB-2 and EB-3 Green Card sponsorship once you're established in the role.
How do I apply for AI ML Engineering jobs at NVIDIA?
Applications go through NVIDIA's careers portal. Most AI ML Engineering roles require a technical screen covering GPU programming, model optimization, or systems design, followed by multiple rounds of interviews. Migrate Mate aggregates NVIDIA's open AI ML Engineering positions filtered by visa sponsorship type, which makes it easier to identify the right roles before applying directly on NVIDIA's site.
What qualifications does NVIDIA look for in AI ML Engineering candidates?
NVIDIA typically expects a bachelor's or master's degree in computer science, electrical engineering, or a closely related field. Practical experience with CUDA, large-scale model training, and inference optimization carries significant weight. For H-1B purposes, your degree field needs to align with the specific role, so a degree in a tangential discipline may require additional documentation showing equivalency.
How long does the visa sponsorship process take when joining NVIDIA?
Timeline depends on your visa category. E-3 consular processing typically takes two to six weeks once your employer files the Labor Condition Application with DOL. H-1B transfers for candidates already in status can take two to four months under standard USCIS processing. Cap-subject H-1B candidates must wait for the October 1 fiscal year start date, meaning an offer signed in spring may not result in a start date until fall.