Fellow, AI Workload Optimization

Advanced Micro Devices, Inc•Bellevue, WA

About The Position

AMD is seeking a technical leader to join its AI Software group as a Fellow. The position defines and drives end-to-end software optimization strategy to achieve industry-leading performance for top-tier customers. It works across architecture, customer engagement, and software engineering to optimize AMD’s software stack—from ROCm and compilers to high-level AI frameworks—for demanding AI workloads.

Requirements

  • Deep software development experience and experience in a high-level technical leadership role, such as Fellow or equivalent.
  • Deep expertise in AI frameworks, including PyTorch, JAX, vLLM, or SGLang, and the ROCm software stack.
  • Proven history of optimizing distributed inference and training at scale across multi-node and multi-GPU environments.
  • Mastery of performance profiling tools such as TorchProfiler, ROCm Profiler, or Nsight, and hardware-level performance modeling.
  • Strong understanding of modern model architectures, including Transformers, Attention, and KV Cache, and techniques such as quantization, speculative decoding, and FlashAttention.
  • Demonstrated ability to drive cross-functional initiatives in fast-paced, ambiguous environments.
  • Demonstrated research or applied AI/ML experience, including deep learning, model training or inference optimization, large language models, or computer vision.

Nice To Haves

  • PhD or Master’s degree in Computer Science, Electrical Engineering, or a related field, or equivalent experience.

Responsibilities

  • Set the technical vision and roadmap for workload optimization across the AI software stack.
  • Lead profiling, analysis, and tuning of large-scale LLM, diffusion, multimodal, and MoE models for performance on AMD hardware.
  • Partner with top customers and hyperscalers to understand workload requirements and deliver tailored architectural improvements and software optimizations.
  • Collaborate with hardware architecture, compiler, and framework teams to influence future silicon features based on evolving AI workload trends.
  • Drive development of tools and frameworks for performance estimation, modeling, and automated reporting.
  • Represent AMD in industry forums and open-source communities.
  • Mentor and inspire AMD technical leaders and engineers.
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