AI Architect Jobs at NVIDIA with Visa Sponsorship
AI Architect jobs at NVIDIA sit at the intersection of large-scale GPU infrastructure, deep learning systems design, and enterprise deployment. NVIDIA has a consistent track record of sponsoring work visas across multiple categories for technical architecture roles, making it a realistic target for international candidates with the right background.
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Get Access To All JobsINTRODUCTION
We are now looking for a Senior AI Training Performance Architect.
NVIDIA is seeking a senior engineer who is obsessed with performance analysis and optimization to help us squeeze every last clock cycle out of AI training, the workload driving the design and construction of the largest and most powerful compute systems in the world. If you are willing to work across all layers of the hardware/software stack - from GPU architecture to the application code - to achieve peak performance, we want to hear from you. This role offers the opportunity to directly impact the hardware and software roadmap in a fast-growing technology company that leads the AI revolution. Join us and help design and build the world's most powerful compute systems!
ROLE AND RESPONSIBILITIES
What you will be doing:
- Understand, analyze, profile, and optimize AI training workloads on state-of-the-art hardware and software platforms.
- Identifying performance bottlenecks of AI training on GPUs, prioritizing and then solving problems across the key AI training workloads.
- Implement production-quality software across multiple layers of NVIDIA's deep learning platform stack, from drivers to DL frameworks.
- Build and support NVIDIA submissions for MLPerf Training benchmarks.
- Implement key DL training workloads in NVIDIA's proprietary processor and system simulators to enable future architecture studies.
- Develop tools to automate workload analysis, optimization, and other critical workflows.
BASIC QUALIFICATIONS
What we want to see:
- PhD in CS, EE or CSEE (or equivalent experience) with 5+ years of relevant experience; or MS with 8+ years of experience.
- Strong background in deep learning and neural networks, particularly in training.
- Solid understanding of computer architecture and familiarity with GPU architecture fundamentals.
- Proven background in analyzing and tuning application performance.
- Proven experience with processor and system-level performance modeling.
- Proficiency in programming with C++, Python, and CUDA.
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 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 July 28, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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
We are now looking for a Senior AI Training Performance Architect.
NVIDIA is seeking a senior engineer who is obsessed with performance analysis and optimization to help us squeeze every last clock cycle out of AI training, the workload driving the design and construction of the largest and most powerful compute systems in the world. If you are willing to work across all layers of the hardware/software stack - from GPU architecture to the application code - to achieve peak performance, we want to hear from you. This role offers the opportunity to directly impact the hardware and software roadmap in a fast-growing technology company that leads the AI revolution. Join us and help design and build the world's most powerful compute systems!
ROLE AND RESPONSIBILITIES
What you will be doing:
- Understand, analyze, profile, and optimize AI training workloads on state-of-the-art hardware and software platforms.
- Identifying performance bottlenecks of AI training on GPUs, prioritizing and then solving problems across the key AI training workloads.
- Implement production-quality software across multiple layers of NVIDIA's deep learning platform stack, from drivers to DL frameworks.
- Build and support NVIDIA submissions for MLPerf Training benchmarks.
- Implement key DL training workloads in NVIDIA's proprietary processor and system simulators to enable future architecture studies.
- Develop tools to automate workload analysis, optimization, and other critical workflows.
BASIC QUALIFICATIONS
What we want to see:
- PhD in CS, EE or CSEE (or equivalent experience) with 5+ years of relevant experience; or MS with 8+ years of experience.
- Strong background in deep learning and neural networks, particularly in training.
- Solid understanding of computer architecture and familiarity with GPU architecture fundamentals.
- Proven background in analyzing and tuning application performance.
- Proven experience with processor and system-level performance modeling.
- Proficiency in programming with C++, Python, and CUDA.
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 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 July 28, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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 AI Architect Jobs at NVIDIA
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Get Access To All JobsTips for Finding AI Architect Jobs at NVIDIA
Align your portfolio to NVIDIA's deployment scale
NVIDIA hires AI Architects who have designed systems at GPU-cluster scale, not just trained models. Document architectures you've built involving distributed inference, CUDA optimization, or multi-node training pipelines before you apply.
Target NVIDIA's enterprise and cloud divisions specifically
NVIDIA's AI Architect openings are concentrated in teams supporting DGX systems, NVIDIA AI Enterprise, and cloud service partnerships. Roles tied to those product lines move through hiring more consistently than exploratory research positions.
Confirm your degree maps to the specialty occupation standard
USCIS requires a direct relationship between your degree field and the role. For AI Architect positions, a degree in computer science, electrical engineering, or a closely related discipline is the safest foundation. A general IT or business degree may require additional documentation.
Negotiate the start date around H-1B cap timing
If you're not already in H-1B status, an October 1 start date is required for cap-subject petitions. Discuss this constraint with your NVIDIA recruiter early so the offer letter and onboarding plan reflect the correct timeline from the start.
Browse AI Architect openings at NVIDIA through Migrate Mate
Filter verified visa-sponsoring openings by role and employer on Migrate Mate to find active AI Architect positions at NVIDIA before applying directly through NVIDIA's career portal.
Prepare for NVIDIA's technical interview structure before discussing visa status
NVIDIA's AI Architect interviews typically include system design rounds focused on inference optimization and deployment architecture. Clear the technical bar first. Visa logistics are handled by a dedicated immigration team after an offer is extended.
Frequently Asked Questions
Does NVIDIA sponsor H-1B visas for AI Architects?
Yes, NVIDIA sponsors H-1B visas for AI Architect roles. NVIDIA works with immigration counsel to file H-1B petitions for qualifying candidates, including both cap-subject registrations and cap-exempt transfers for candidates already holding H-1B status with another employer. If you're in the H-1B lottery pool, NVIDIA's size and resourcing means the process is well-structured once an offer is made.
How do I apply for AI Architect jobs at NVIDIA?
Apply directly through NVIDIA's careers portal, targeting roles in AI infrastructure, enterprise AI, or cloud solutions architecture. Tailor your resume to reflect GPU-scale system design and deployment experience. You can also browse verified AI Architect openings at NVIDIA on Migrate Mate, which surfaces roles from employers with confirmed sponsorship track records so you're not applying blind on sponsorship eligibility.
Which visa types does NVIDIA commonly use for AI Architect roles?
NVIDIA sponsors H-1B visas for most international AI Architect hires. Australian citizens can pursue the E-3 visa, which bypasses the H-1B lottery entirely and allows year-round applications. For candidates seeking permanent residence, NVIDIA supports EB-2 and EB-3 Green Card sponsorship, typically beginning the PERM labor certification process after an employee has established tenure in the role.
What qualifications does NVIDIA expect for AI Architect roles?
NVIDIA generally expects a bachelor's or master's degree in computer science, electrical engineering, or a related field, combined with hands-on experience designing large-scale AI systems. Practical depth in CUDA, TensorRT, distributed training frameworks like PyTorch or JAX, and deployment on NVIDIA hardware platforms carries significant weight. Candidates who have architected inference pipelines at production scale stand out in NVIDIA's hiring process.
How do I plan the timeline for an AI Architect role at NVIDIA if I need visa sponsorship?
If you need a new H-1B, the cap registration window runs in March for an October 1 start date, so factor roughly six to seven months between offer and day one. E-3 visa applicants typically move faster, with consular processing taking two to four weeks. For candidates transferring an existing H-1B, NVIDIA can file a portability petition and you can start shortly after filing, before USCIS adjudicates.