Senior GPU Performance Engineer - AI Workloads

Advanced Micro Devices, Inc • Santa Clara, CA

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About The Position

AMD is seeking a GPU Performance Engineer to optimize AI workloads and help guide the evolution of next-generation AMD Instinct GPU architectures. The role works across the software and hardware stack, performing deep GPU kernel-level performance analysis, identifying microarchitectural bottlenecks, and driving low-level kernel optimizations for foundation model workloads on large-scale GPU systems. The engineer collaborates with kernel, framework, distributed systems, compiler/runtime, and hardware architecture teams to improve current AI performance and inform future GPU designs.

Requirements

• MS or PhD in Computer Science, Computer Engineering, or a related technical field.
• Strong hands-on experience in GPU kernel-level performance analysis and low-level optimization using CUDA, HIP/ROCm, or equivalent technologies.
• Deep understanding of GPU microarchitecture, including execution pipelines, SIMD/SIMT scheduling, registers, memory hierarchy, caches, and interconnects.
• Experience using performance counters, thread traces, profilers, and ISA/assembly analysis to root-cause GPU kernel performance bottlenecks.
• Hands-on experience optimizing performance-critical GPU kernels and developing targeted microbenchmarks or reproducer kernels.
• Proficiency in C++ and GPU kernel programming, with Python experience for performance analysis and automation.
• Advanced Linux OS, container technologies such as Docker, and Git/GitHub skills.
• Familiarity with AI workloads, AI frameworks, distributed computing, and communication libraries such as PyTorch, JAX, Megatron-LM, NCCL/RCCL, and MPI.

Nice To Haves

• Strong track record of delivering GPU kernel performance improvements through low-level hardware/software analysis and optimization.
• Experience working across kernel, compiler/runtime, framework, distributed systems, and GPU architecture teams to resolve complex performance bottlenecks.
• Experience analyzing large-scale AI workloads and translating workload-level performance gaps into actionable kernel, software-stack, or microarchitecture improvements.

Responsibilities

• Profile and optimize large-scale AI workloads—including transformers, multimodal models, diffusion models, and recommender systems—across multi-node, multi-GPU systems.
• Analyze GPU kernels to identify bottlenecks in compute pipelines, memory hierarchy, instruction execution, synchronization, and data movement.
• Root-cause performance gaps using GPU performance counters, thread traces, ISA/assembly analysis, and targeted microbenchmarks, and deliver low-level kernel optimizations.
• Collaborate with kernel, compiler, runtime, framework, and distributed systems teams to improve kernel performance, scheduling, memory utilization, and system-level efficiency.
• Develop and maintain benchmarks, microbenchmarks, and traces representative of foundation model and broader AI workloads.
• Provide kernel- and microarchitecture-level performance insights to AMD Instinct GPU architecture teams to inform hardware/software co-design decisions for future architectures.
• Present findings to cross-functional teams and leadership, shaping software and hardware roadmaps.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior