GPU Architecture and AI Performance Simulation Engineer

About the role

We are looking for a talented and motivated GPU Architecture and AI Performance Simulation Engineer. The role sits at the intersection of AI workloads and next-generation GPU hardware - analyzing, modeling, and optimizing AI workload performance on GPU and SoC architectures to shape architectural decisions across current and future silicon.

What you'll do

• Analyze AI workload behavior on GPU architectures - distinguishing compute-bound, memory-bound
• Build and maintain roofline analytical models and cycle-accurate performance models to support hardware what-if studies and guide micro-architectural decisions
• Analyze AI workloads built on Transformer and Mixture-of-Experts (MoE) architectures, inference and training
• Model and analyze multi-GPU and at-scale AI systems - workload distribution, synchronization overhead, and communication-compute overlap
• Guide and mentor the team in delivering analytical models and end-to-end system-level performance projections

What you need

• 10–18 years in electrical & electronics
• LLMs
• IPR
• PyTorch
• TensorFlow
• PhD