Compute System Arch AI Infra Intern - 2027
At a glance
Junior ML Platform & Ops role at NVIDIA. China, Shanghai · full-time.
Pay not stated ML Platform & Ops salary
aimlroles summary, based on the employer's posting.
What you'll do
- Learn the team’s compute architecture work, existing AI systems and workflows, and the needs those systems must meet
- Shape an AI infrastructure design with your mentor, then build it to match the agreed plan
- Gather test scenarios and use them to check the implementation before handing it over
- Prepare clear handoff documentation, record user feedback, and suggest improvements with your mentor
- Write a project summary covering the work
What you bring
- You are pursuing a bachelor’s degree in computer science or electrical engineering
- You communicate and collaborate well, with strong analysis and practical problem-solving ability
- You have experience building AI-integrated workflows and familiarity with AI-assisted development
Who this fits
This internship suits someone who wants hands-on AI infrastructure work and can collaborate closely with a mentor. Graduate study, RAG or AI agent development, and GPU architecture or full-chip verification experience can strengthen your fit.
From the employer
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.