Principal Software Development Engineer, AI Performance

Amd

Hybrid

Quick summary

Work type
Hybrid
Location
San Jose, CA
Posted
122 days ago
Closes
Feb 26, 2027

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Similar $202k
$155k most similar roles pay here $248k

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About Amd

AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors

Amd currently has 56 open roles on FindRole.

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TL;DR · Principal Software Development Engineer, AI Performance

AMD seeks a Principal Engineer to lead a team driving the performance and scalability of AI workloads on AMD GPUs, focusing on large language models and advanced architectures. This role involves setting technical direction, making critical architecture decisions, and optimizing GPU kernels and serving frameworks. The ideal candidate has over 10 years of experience in GPU computing, HPC, or AI systems, with expertise in GPU micro-architecture, memory hierarchy, and performance engineering. Proficiency in C++, Python, and tools like HIP, CUDA, and LLVM is essential, along with hands-on contributions to open-source frameworks such as PyTorch and vLLM. The candidate should also have a strong background in multi-GPU communication and system-level design, influencing technical direction across teams while mentoring engineers and raising the technical bar within AMD.

What you'll do

  • Define and drive long-term technical strategy for AI workload performance on AMD GPUs.
  • Own complex cross-stack performance challenges from kernel optimization to framework-level architecture decisions.
  • Lead design and implementation of novel GPU kernels, compiler optimizations, and framework features.
  • Establish performance methodology and roofline analysis practices setting the standard for the team.
  • Influence upstream roadmaps in major open-source AI frameworks like vLLM and PyTorch.

What we're looking for

  • 10+ years of experience in GPU computing, HPC, or AI systems
  • Deep understanding of GPU micro-architecture and end-to-end AI systems
  • Experience designing and optimizing across the full stack from low-level kernels to frameworks
  • Strong background in performance engineering including profiling and roofline analysis
  • Hands-on experience with major open-source AI frameworks and GPU compiler toolchains
  • Track record of leading small technical teams while remaining hands-on
  • Master's or PhD in Computer Science, Engineering, or related field

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