INTERNSHIP DETAILS

Compute System Arch AI Infra Intern - 2027

CompanyNVIDIA
LocationShanghai
Work ModeOn Site
PostedSeptember 5, 2026
Internship Information
Core Responsibilities
The intern will design, implement, and verify AI infrastructure for GPU compute systems while collaborating with mentors to improve development flows. They will also be responsible for documenting processes, collecting user feedback, and debugging hardware function bugs.
Internship Type
full time
Company Size
51790
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

Compute System Architect team’s work scope covers whole compute pipeline, memory system and multi GPU, CPU and CPU interconnection, which provides good opportunity to deeply learn the latest cross unit new features in the new GPU architectures. The team works as the safety net of the chip. We catch function bugs in the HW by randomly generating tests and running them in various pre-silicon and post-silicon full chip platforms and debugging the failures. This works provides a good full chip view of GPU and has a big space to innovate.

What you’ll be doing:

  • Get familiar with Compute System Architect’s daily work as background knowledge

  • Get familiar with the team’s existing AI infrastructure and flows

  • Get a clear understanding of the AI infra requirement

  • Co-work with mentor to propose, review and finalize the design for the AI infra

  • Efficiently implement the AI infra according to the design

  • Actively collect testing use cases for the AI infra and use them to verify the implemention

  • Deliver the AI infra to the team with well organized documentation

  • Collect and document feedback from users

  • Proactively discuss improvement opportunities with mentor

  • Provide a summary report out for the project

What we need to see:

  • Good at communication and collaboration

  • Demonstrates strong analytical skills and a proven capacity for effective problem solving

  • Familiar with AI assisted development

  • Experience of building AI integrated flows

  • Pursuing a Bachelor in CS or EE. MS, PhD is a plus.

Ways to stand out from the crowd:

  • Experience of building RAG and AI agent can be useful

  • Knowledge of GPU architecture and/or experience of full chip verification is helpful

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you.

Key Skills
Compute System ArchitectureGPU ArchitectureAI InfrastructureFull Chip VerificationHardware DebuggingAI Assisted DevelopmentRAGAI AgentsAnalytical SkillsProblem SolvingCommunicationCollaborationPre-silicon TestingPost-silicon Testing
Categories
TechnologyEngineeringSoftwareData & Analytics