INTERNSHIP DETAILS

Computer Architecture Intern - 2026

CompanyNVIDIA
LocationBeijing
Work ModeOn Site
PostedMarch 6, 2026
Internship Information
Core Responsibilities
Interns will be responsible for enhancing GPU architecture to advance state-of-the-art performance, efficiency, and reliability, while also analyzing, tuning, and prototyping key applications for new GPU architectures. Key tasks include building models to predict future architecture performance and designing tools for application performance and energy consumption analysis.
Internship Type
full time
Company Size
46209
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.
About the Role

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

#deeplearning
Key Skills
CC++Computer ArchitectureParallel ProcessingHigh Performance ComputingPerformance ModelingPower ModelingReliability ModelingGPU ArchitectureSimulationValidationVerification
Categories
EngineeringScience & ResearchSoftwareTechnologyData & Analytics