Computer Architecture Intern - 2026
at Nvidia
Posted 4 hours ago
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- Compensation
- Not specified
- City
- Shanghai
- Country
- China
Currency: Not specified
Join NVIDIA's Architecture group as a Computer Architecture Intern to work on cutting-edge GPU architecture research. You will enhance GPU architecture for performance, efficiency, programmability, and reliability; analyze and prototype key applications for new architectures; and build models to predict performance, power, and reliability on future hardware. You will also design and develop tools to analyze, simulate, validate, and verify application performance and energy consumption, and collaborate with software, research, and product teams to steer GPU computing directions.
We are now looking for Computer Architecture Interns in our group!
The NVIDIA Architecture group is looking for world class architects and computer science interns to join and lead our various architecture efforts. A key part of NVIDIA's strength is to innovate in the graphics and parallel computing fields delivering the highest performance in the world for parallel processing algorithms. We are constantly looking for ways to improve our GPU architecture and maintain our leadership by developing new parallel programming models, new architectures and new infrastructure that is required to make this successful.
What you'll be doing:
Enhance GPU architecture to extend the state of the art in performance, efficiency, programmability and reliability
Analyze, tune and prototype key applications for new GPU architectures
Build model to predict performance, power and reliability on future architecture
Design and develop tools to analyze, simulate, validate, and verify application performance and energy consumption
Collaborate across the company to guide the direction of GPU computing, working with software, research and product team
What we need to see:
Pursuing MS Degree in relevant discipline (CS, EE, Math). PhD helpful
Expert programming skills in C or C++
Strong background in computer architecture, parallel processing, signal processing and/or high performance computing
Experience in characterizing and modeling system-level performance or power, executing comparison studies, and documenting and publishing results
Ways to stand out from the crowd:
Optional/Plus -- Background in computer vision, machine learning, or any HPC domain

