GPU Performance Architect - Shape Next-Gen AI GPUs

Socket.dev

Santa Clara (CA)

On-site

USD 180,000 - 260,000

Full time

14 days+
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Job summary

AMD's Radeon Technologies Group is seeking a GPU Performance Architect in Santa Clara, CA. You will analyze workloads, identify bottlenecks in graphics cores, and work with architects to drive PPA improvements on next-gen GPUs. Engage with teams across sites to deliver high-impact results.

Ideal candidates have deep experience in GPU architecture, AI/ML algorithms, and GPU performance tooling. Strong C/C++ and Python scripting skills, plus DirectX/Vulkan/CUDA/HIP familiarity, are essential.

Qualifications

  • Undergrad degree in EE/CS/Computer Architecture is required.
  • Master's/PhD with emphasis in EE/CS preferred.
  • Experience across architecture, performance analysis and AI/ML/graphics algorithms.

Responsibilities

  • Analyze workloads and game/AI/ML performance across current and future GPUs.
  • Identify bottlenecks in graphics cores and SoCs and propose solutions.
  • Collaborate with architects to drive RTG analysis improvements.
  • Develop and run RTL and high-level simulation models to estimate gains.
  • Drive initiatives to improve RTG tooling and workflows.
  • Work with teams across multiple sites to deliver results.

Skills

GPU architecture & compilers
LLM kernel development
C/C++/Python scripting
Graphics/Compute APIs
AI/ML/graphics algorithms
GFX profiling tools

Education

Bachelor's degree in Electrical Engineering/Computer Architecture/CS
Master's or PhD preferred

Job description

AMD's Radeon Technologies Group is seeking a GPU Performance Architect in Santa Clara, CA. You will analyze workloads, identify bottlenecks in graphics cores, and work with architects to drive PPA improvements on next-gen GPUs. Engage with teams across sites to deliver high-impact results.

Ideal candidates have deep experience in GPU architecture, AI/ML algorithms, and GPU performance tooling. Strong C/C++ and Python scripting skills, plus DirectX/Vulkan/CUDA/HIP familiarity, are essential.

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