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 compositionLearn about what’s the usual feature metrics for GPU workloadDesign and implement inventive solution to efficiently extract features from GPU workloadVerify the solution using direct and random GPU workloadDesign and implement inventive solution simplify GPU workload while keeping the required featuresDesign and implement inventive solution to generate GPU workload according to required featuresDesign and implement inventive solution to generate GPU workload which has the same feature with a given test and randomize other (required) featuresThoroughly 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 abilityShown knowledge of DL algorithmsExperience of training and fine-tuning modelExperience of building and improving own modelBachelor in CS or EE. MS, PhD or equivalent is a plus.Ways to stand out from the crowd:Knowledge of GPU architectureExperience of building AI agentNVIDIA 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.