NVIDIA Visa Sponsorship Jobs USA
NVIDIA is one of the most active visa sponsors in the technology sector, with a strong track record across H-1B visa, E-3 visa, and Green Card pathways. For international professionals targeting roles in AI, semiconductors, and high-performance computing, NVIDIA is a compelling employer with a well-established sponsorship program.
See All NVIDIA JobsOverview
Showing 5 of 562+ NVIDIA Visa Sponsorship Jobs USA
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 562+ NVIDIA Visa Sponsorship Jobs USA
Sign up for free to unlock all listings, filter by visa type, and get alerts for new NVIDIA Visa Sponsorship Jobs USA.
Get Access To All JobsINTRODUCTION
NVIDIA is seeking an NCX Engineer, AI Accelerator to join our AI Accelerator team, collaborating closely with strategic customers to implement and enhance groundbreaking AI workloads! You will deliver hands-on technical assistance for advanced AI deployments, intricate distributed systems, and ensure customers realize efficient performance from NVIDIA's AI platform across varied environments. We partner with the world's most innovative AI companies to address their most challenging technical problems.
ROLE AND RESPONSIBILITIES
In this role, you will develop innovative solutions that advance AI infrastructure capabilities. You will directly influence customer success with breakthrough AI initiatives.
- Build and deploy custom AI solutions on NCP and Neo Cloud platforms, including distributed training, inference optimization, and MLOps pipelines constructed on NVIDIA reference architectures.
- Act as the main technical contact for strategic NCPs, offer remote and on-site support, troubleshoot complex production problems, and guide partner engineering teams on NVIDIA platform guidelines.
- Deploy and manage AI workloads across DGX Cloud, NCP data centers, and major CSP environments using Kubernetes, containers, and GPU scheduling systems aligned to NCP builds.
- Profile and tune large-scale training and inference workloads on NCP platforms. Implement observability and SLO/SLA monitoring. Lead detailed efforts to reduce latency, cost, and operational risk.
- Implement and expand NVIDIA reference architectures on partner platforms, develop integrations with partner control planes and customer environments, and ensure smooth API, data pipeline, and enterprise software connectivity.
- Build detailed implementation guides, runbooks, and post-mortem documentation that codify standard methodologies for running NVIDIA AI workloads at scale on NCP platforms.
BASIC QUALIFICATIONS
- BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
- 8+ years of experience in customer facing technical roles such as Solutions Engineering, DevOps, Site Reliability, or ML Infrastructure Engineering, ideally supporting large-scale cloud or service provider environments.
- Strong expertise in Linux systems, distributed computing, Kubernetes, containers, and GPU scheduling on multi-tenant or service-provider platforms.
- Demonstrated AI/ML experience supporting large-scale training and inference workloads (e.g., LLMs, generative models, recommendation systems) in production or critically important environments.
- Solid programming skills in Python/Go, with hands-on experience using frameworks such as PyTorch or TensorFlow for training and serving.
- Demonstrated capability to collaborate with customer and partner engineering teams in fast-paced environments, guide intricate technical investigations, and bring issues to root cause and resolution.
- Excellent communication and technical presentation skills, with the ability to clearly articulate architectures, trade-offs, and recommendations to both engineering and leadership audiences.
PREFERRED QUALIFICATIONS
- Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, Triton, NIM, and NVIDIA networking technologies such as InfiniBand and RoCE.
- Direct experience collaborating with NVIDIA Cloud Partners, hyperscale CSPs, or managed AI cloud platforms, including implementation of NVIDIA reference architectures for AI infrastructure.
- Deep familiarity with MLOps and cloud-native practices: containerization, CI/CD pipelines, observability stacks (Prometheus, Grafana, OpenTelemetry), and GitOps workflows.
- Background in infrastructure as code (Terraform, Ansible, or similar) for repeatable deployment and configuration of GPU-accelerated clusters and NCP building blocks.
- Experience integrating AI platforms with enterprise systems such as Salesforce, ServiceNow, or other ITSM/CRM platforms to support end-to-end customer solutions and managed services.
NVIDIA offers competitive salaries and a generous benefits package. It is recognized as one of the technology world’s most desirable employers. We have some of the most innovative and dedicated people working here. Due to rapid growth, our outstanding teams are expanding quickly. Join us to make a lasting impact on the world!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 9, 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 is seeking an NCX Engineer, AI Accelerator to join our AI Accelerator team, collaborating closely with strategic customers to implement and enhance groundbreaking AI workloads! You will deliver hands-on technical assistance for advanced AI deployments, intricate distributed systems, and ensure customers realize efficient performance from NVIDIA's AI platform across varied environments. We partner with the world's most innovative AI companies to address their most challenging technical problems.
ROLE AND RESPONSIBILITIES
In this role, you will develop innovative solutions that advance AI infrastructure capabilities. You will directly influence customer success with breakthrough AI initiatives.
- Build and deploy custom AI solutions on NCP and Neo Cloud platforms, including distributed training, inference optimization, and MLOps pipelines constructed on NVIDIA reference architectures.
- Act as the main technical contact for strategic NCPs, offer remote and on-site support, troubleshoot complex production problems, and guide partner engineering teams on NVIDIA platform guidelines.
- Deploy and manage AI workloads across DGX Cloud, NCP data centers, and major CSP environments using Kubernetes, containers, and GPU scheduling systems aligned to NCP builds.
- Profile and tune large-scale training and inference workloads on NCP platforms. Implement observability and SLO/SLA monitoring. Lead detailed efforts to reduce latency, cost, and operational risk.
- Implement and expand NVIDIA reference architectures on partner platforms, develop integrations with partner control planes and customer environments, and ensure smooth API, data pipeline, and enterprise software connectivity.
- Build detailed implementation guides, runbooks, and post-mortem documentation that codify standard methodologies for running NVIDIA AI workloads at scale on NCP platforms.
BASIC QUALIFICATIONS
- BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
- 8+ years of experience in customer facing technical roles such as Solutions Engineering, DevOps, Site Reliability, or ML Infrastructure Engineering, ideally supporting large-scale cloud or service provider environments.
- Strong expertise in Linux systems, distributed computing, Kubernetes, containers, and GPU scheduling on multi-tenant or service-provider platforms.
- Demonstrated AI/ML experience supporting large-scale training and inference workloads (e.g., LLMs, generative models, recommendation systems) in production or critically important environments.
- Solid programming skills in Python/Go, with hands-on experience using frameworks such as PyTorch or TensorFlow for training and serving.
- Demonstrated capability to collaborate with customer and partner engineering teams in fast-paced environments, guide intricate technical investigations, and bring issues to root cause and resolution.
- Excellent communication and technical presentation skills, with the ability to clearly articulate architectures, trade-offs, and recommendations to both engineering and leadership audiences.
PREFERRED QUALIFICATIONS
- Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, Triton, NIM, and NVIDIA networking technologies such as InfiniBand and RoCE.
- Direct experience collaborating with NVIDIA Cloud Partners, hyperscale CSPs, or managed AI cloud platforms, including implementation of NVIDIA reference architectures for AI infrastructure.
- Deep familiarity with MLOps and cloud-native practices: containerization, CI/CD pipelines, observability stacks (Prometheus, Grafana, OpenTelemetry), and GitOps workflows.
- Background in infrastructure as code (Terraform, Ansible, or similar) for repeatable deployment and configuration of GPU-accelerated clusters and NCP building blocks.
- Experience integrating AI platforms with enterprise systems such as Salesforce, ServiceNow, or other ITSM/CRM platforms to support end-to-end customer solutions and managed services.
NVIDIA offers competitive salaries and a generous benefits package. It is recognized as one of the technology world’s most desirable employers. We have some of the most innovative and dedicated people working here. Due to rapid growth, our outstanding teams are expanding quickly. Join us to make a lasting impact on the world!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 9, 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.
Job Roles at NVIDIA
See all 562+ NVIDIA jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new NVIDIA roles.
Get Access To All JobsTips for Finding NVIDIA Visa Sponsorship Jobs USA
Target engineering and research roles first
NVIDIA's sponsorship activity is concentrated in deeply technical roles, GPU architecture, AI research, and systems engineering. Applying to these teams gives you the strongest alignment with where NVIDIA has historically invested in international talent.
Understand the specialty occupation standard early
NVIDIA files H-1B petitions for roles requiring specialized technical degrees. Before applying, confirm your degree field directly matches the role, a mismatch here is the most common reason petitions face scrutiny in high-tech filings.
Australian citizens should ask about E-3 sponsorship
NVIDIA sponsors E-3 visas, which are available exclusively to Australian citizens. If you hold an Australian passport, the E-3 avoids the H-1B lottery entirely, worth raising explicitly during your recruiter conversation rather than assuming it's on their radar.
Factor in Green Card timelines when evaluating offers
NVIDIA has a strong Green Card sponsorship history, which matters for long-term planning. Ask your recruiter whether the role is eligible for employer-sponsored permanent residence and how early in your tenure that process typically begins.
Apply well before H-1B registration opens in March
NVIDIA recruits for sponsored roles throughout the year, but positions tied to the H-1B cap fill early. Getting your application in by late 2025 for a 2026 start gives you the best chance of having an approved offer before registration closes.
Use verified sponsorship data to find open roles
Not every NVIDIA job posting explicitly mentions visa sponsorship. Migrate Mate surfaces verified sponsors so you can filter by real sponsorship history and find NVIDIA roles confirmed to support international candidates, without guessing from job descriptions alone.
NVIDIA jobs are hiring across the US. Find yours.
Find NVIDIA JobsFrequently Asked Questions
Does NVIDIA sponsor H-1B visas?
Yes, NVIDIA sponsors H-1B visas and is one of the most active sponsors in the technology sector. Sponsorship is concentrated in engineering, AI research, and computing-intensive roles that require a degree in a specific technical field. The H-1B is the primary pathway for non-Australian international professionals joining NVIDIA in the United States.
Which visa types does NVIDIA sponsor?
NVIDIA sponsors H-1B visas for specialty occupation roles, E-3 visas for Australian citizens, and employer-sponsored Green Cards through the EB-2 and EB-3 preference categories. The Green Card pathway is particularly relevant for candidates planning long-term careers at NVIDIA, as the company has a strong track record of supporting permanent residence for international employees.
Which departments or roles at NVIDIA are most likely to receive visa sponsorship?
Sponsorship at NVIDIA is most common in highly technical functions, including GPU and chip architecture, deep learning research, software engineering for CUDA and AI frameworks, and hardware design. Roles requiring a graduate degree in computer science, electrical engineering, or a closely related field tend to have the strongest alignment with NVIDIA's sponsorship activity.
How do I find visa-sponsored job openings at NVIDIA?
Not all NVIDIA job postings clearly state whether sponsorship is available, which makes it easy to miss eligible roles. Migrate Mate aggregates verified sponsorship data so you can browse NVIDIA openings confirmed to support H-1B, E-3, or Green Card candidates, saving you the guesswork of decoding each job description individually.
How do I time my application to NVIDIA for H-1B sponsorship?
The H-1B cap registration window opens each March for an October 1 start date. NVIDIA typically recruits sponsored roles months in advance. Applying in late fall or early winter for the following cycle gives your application the best chance of moving through interviews, offer, and USCIS petition filing before the registration deadline closes.
See which NVIDIA employers are hiring and sponsoring visas right now.
Search NVIDIA Jobs