Senior Staff Compiler Software Engineer

Advance Your Career. Advance The World.

At AMD, we believe technology can change lives for the better. It can heal us, entertain us, and make us more connected, productive, and understanding of the world around us. And we're looking for talent who feel the same: people who want to leave the planet better than they found it, those who don't shy away from humanity's challenges but are determined to help solve them.

AMD is powering the next generation of supercomputing, high-performance computing, cloud, and AI. Whether you're designing next-gen processors, enabling AI breakthroughs, or creating go-to-market plans, every role at AMD contributes to something bigger — technology that moves the world forward.

AMD is seeking a Senior Staff Software Engineer to lead compiler development and GPU performance optimization for next-generation AI and compute platforms. You will design compiler technologies using MLIR and LLVM, develop optimized code-generation flows, and work closely with GPU architecture, runtime, and AI framework teams to deliver industry-leading performance.

The ideal candidate is an experienced technical leader with deep expertise in compiler design, GPU architecture, and performance optimization. You can work across the full compiler stack—from high-level graph and tensor transformations to low-level GPU code generation and kernel tuning. You are comfortable solving complex system problems, influencing technical direction across teams, and applying AI-assisted tools to improve compiler engineering.

• Design and implement compiler optimizations using MLIR and LLVM for GPU and AI workloads.
• Develop compiler passes, intermediate representations, lowering pipelines, and target-specific code generation.
• Optimize graph transformations, operator fusion, tiling, vectorization, memory planning, and kernel scheduling.
• Analyze generated GPU code and tune kernels for compute utilization, memory bandwidth, cache efficiency, occupancy, and synchronization.
• Perform end-to-end performance analysis across AI frameworks, compilers, runtimes, libraries, and GPU hardware.
• Collaborate with GPU architecture teams to enable new hardware features and drive hardware-software co-design.
• Build profiling, benchmarking, autotuning, and performance-regression infrastructure.
• Apply AI and coding agents to compiler development, kernel optimization, debugging, test generation, and performance analysis.
• Provide technical leadership, drive architecture decisions, and mentor engineers across compiler and GPU projects.

• Deep hands-on experience with MLIR, LLVM, compiler optimization, lowering, and code generation.
• Strong knowledge of compiler architecture, intermediate representations, transformation passes, and optimization pipelines.
• Strong understanding of GPU architecture, including parallel execution, memory hierarchy, caches, registers, synchronization, and occupancy.
• Advanced C/C++ skills with experience in HIP, CUDA, or similar GPU programming models.
• Proven experience profiling and optimizing GPU kernels or compute-intensive AI workloads.
• Experience with AI compilers, tensor or graph compilers, machine learning frameworks, or high-performance computing.
• Demonstrated ability to lead complex technical initiatives and deliver measurable improvements in latency, throughput, and hardware utilization.
• Experience using AI-assisted development tools or applying AI to compiler and kernel optimization.

Bachelor's, Master's, or Doctorate degree in Computer Science, Computer Engineering, or a related field, or equivalent industry experience.

Location:

San Jose, California