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.