GPU Architecture and AI Performance Simulation Engineer

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Descrizione

Job Details: Job Description: 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. The candidate will guide the team in fine-tuning workload, SoC, and system models, propose data-backed architectural enhancements, and track the AI GPU market to inform Intel's future accelerator roadmap. Strong analytical skills, the ability to present performance findings and trade-offs to engineering and leadership teams, and a willingness to mentor peers are essential. Key Responsibilities • Analyze AI workload behavior on GPU architectures - distinguishing compute-bound, memory-bound, and cache-bound behavior to identify performance bottlenecks and optimization opportunities. • 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, and assess the hardware-utilization impact of kernel-level optimizations such as Flash Attention, Flash Decode, Sparse Attention, and Causal Masking. • Model and analyze multi-GPU and at-scale AI systems - workload distribution, synchronization over

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