Fellow, AI Workload Optimization

What you'll do

• Define and drive the end-to-end software optimization strategy for high-performance AI workloads.
• Lead the profiling, analysis, and tuning of large-scale models like LLMs and Diffusion models.
• Partner with top customers and hyperscalers to deliver tailored architectural wins and optimizations.
• Influence future silicon features by collaborating across hardware architecture, compiler, and framework teams.
• Drive the development of advanced tools for performance estimation, modeling, and automated reporting.
• Act as a technical ambassador in industry forums and open-source communities.
• Mentor and inspire the next generation of AMD engineers and technical leaders.

What we're looking for

• Experience in a high-level technical leadership role such as Fellow or equivalent.
• Expertise in AI Frameworks including PyTorch, JAX, vLLM, and SGLang.
• Proficiency with the ROCm software stack.
• Proven experience optimizing distributed inference and training across multi-node/multi-GPU environments.
• Mastery of performance profiling tools such as TorchProfiler, ROCm Profiler, and Nsight.
• Deep understanding of modern model architectures and optimization techniques like quantization and FlashAttention.
• A PhD or Master’s degree in Computer Science, Electrical Engineering, or a related field.
• Demonstrated research or applied experience in AI/ML fields including deep learning and large language models.