Fellow Software Development Engineer, GEMM Optimization

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AMD is seeking a Fellow Software Development Engineer to architect and develop features in the tensile-lite assembly code generator for General Matrix Multiplication (GEMM) and GEMM + X (including attention). GEMM performance is one of the most critical levers for AI workload efficiency and this role sits at the center of AMD's effort to deliver best-in-class matrix-multiply performance across current and next-generation hardware.

You will own the deep, hardware-aware optimization work that turns AMD's GPU architecture into delivered performance: understanding the hardware specification at the instruction and pipeline level, partnering directly with hardware architects to influence future designs, and innovating algorithms to extract maximum throughput.

This role is a strong fit for an engineer who wants to work at the intersection of GPU microarchitecture, low-level code generation, and applied AI performance — someone equally comfortable reading a hardware spec, writing hand-tuned assembly, and explaining a performance tradeoff to a customer or an architect.

• Analyze AMD GPU hardware specifications in depth and work closely with hardware architects to align kernel design with current silicon capabilities and to influence requirements for future generations.
• Develop support for new ISA and HW/SW optimization features in the code-generator
• Innovate and implement new algorithms for implementing GEMM and GEMM + X
• Profile and root-cause GEMM performance bottlenecks across the stack
• Partner with customers and internal stakeholders to understand real-world workload requirements, reproduce performance issues, and deliver targeted performance

• Strong command of GPU computer architecture: compute units, register files, cache/LDS hierarchies, memory bandwidth, matrix cores/WMMA-style instructions, and instruction scheduling/latency hiding.
• Deep expertise in GEMM algorithms and their mapping onto GPU hardware (tiling, blocking, register/LDS allocation, wave scheduling, memory hierarchy utilization).
• Strong software engineering fundamentals with a track record of building production-quality, high-performance software.
• Demonstrated experience optimizing GPU compute kernels, ideally GEMM and attention
• Proficiency in C++ and assembly-level GPU programming; working knowledge of Python for tooling/automation.
• Solid understanding of parallel computing, memory hierarchies, and hardware-software performance tradeoffs.
• Clear written and verbal communication skills; ability to work effectively with hardware architects, customers, and cross-functional engineering teams.
• Direct experience with any GPU compiler backend
• Experience with AMD GPU architectures (CDNA/RDNA) or comparable competitive architectures (NVIDIA Hopper/Blackwell, etc.)
• Contributions to industry standards, publications, or patents related to GPU compute or matrix-multiply optimization

BS/MS/PHD in CS/CE or related field with deep relevant experience

San Jose, CA

Benefits offered are described: AMD benefits at a glance.

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