GPU System Architect team’s work scope covers whole GPU pipeline(graphics, 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 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 various GPU workload’s composition
Learn about what’s the usual feature metrics for GPU workload
Design and implement inventive solution to efficiently extract features from GPU workload
Verify the solution using direct and random GPU workload
Design and implement inventive solution simplify GPU workload while keeping the required features
Design and implement inventive solution to generate GPU workload according to required features
Design and implement inventive solution to generate GPU workload which has the same feature with a given test and randomize other (required) features
Thoroughly verify the solution on GPU functional simulator/full chip RTL/emulation/silicon platform.
Provide detailed and organized documentation and report out for the project.

What we need to see:

Good communication and problem analysis ability
Shown knowledge of DL algorithms
Experience of training and fine-tuning model
Experience of building and improving own model
Bachelor in CS or EE. MS, PhD or equivalent is a plus.

Ways to stand out from the crowd:

Knowledge of GPU architecture
Experience of building AI agent

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.

GPU Workload Analysis Intern - 2026