About the role
NVIDIA's GPU Architecture Group seeks new college graduates to join the team that designs and validates GPU profiling and performance telemetry features. You'll contribute to hardware modeling, test development, and infrastructure — with increasing opportunities to influence the design of the world's leading AI platform.
Join our tight group spanning architecture, ASIC design, performance engineering, drivers, and tools to become a part of the extreme hardware-software codesign process that makes NVIDIA's world-leading AI platform possible!
What you'll be doing:
Build and maintain functional and performance models for GPU hardware features
Write and execute test plans to validate designs across configurations
Contribute to infrastructure that supports the hardware development process
Collaborate with architects, ASIC designers, and software engineers across teams
Develop deep knowledge of GPU architecture and the performance analysis domain
What we need to see:
Pursuing or recently completed a M.S. or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field or equivalent experience (recent graduate or graduating by summer 2026)
Foundation in computer architecture and AI workload acceleration
Programming skills in C++ and Python
Coursework or project experience in performance modeling, hardware simulation, or verification
Strong communication skills for working across multi-functional teams
Ways to stand out from the crowd:
Experience with SystemC or other hardware modeling frameworks
Research in GPU architecture or AI acceleration
Hands-on experience with CUDA or other accelerated computing programming models
Contributions to hardware or architecture projects (academic or open source)
Familiarity with profiling tools or performance analysis
NVIDIA is widely considered one of the technology world's most desirable employers. We work on problems that matter — and we do it with some of the most skilled engineers in the world. If you're analytically sharp, intellectually curious, and ready to have real impact, 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 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.
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.Aplyr's read
NVIDIA is a pioneering force in GPUs and AI, attracting top talent in engineering and innovation-driven roles across various tech domains.
What's promising
- •NVIDIA leads the GPU market, crucial for gaming and AI applications.
- •The company invests heavily in AI and deep learning, driving technological advancements.
- •NVIDIA's strong market position offers stability and growth opportunities for employees.
What to watch
- •High competition in the semiconductor industry can impact market share.
- •Rapid technological changes require constant adaptation and learning.
- •Intense workload and high expectations may affect work-life balance.
Why NVIDIA
- •NVIDIA's GPUs are industry benchmarks in gaming and professional graphics.
- •The company's AI research is at the forefront of deep learning innovation.
- •NVIDIA's culture emphasizes cutting-edge technology and engineering excellence.
Aplyr’s read is generated by AI from public sources. Was it useful?
About NVIDIA
NVIDIA is a leading technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as its advancements in artificial intelligence and deep learning.