About the job
AMD is building the next generation of compiler and software infrastructure to accelerate Large Language Models (LLMs) and ML workloads on emerging accelerator architectures. We are looking for a Principal Software Development Engineer to lead technical development in compiler technology, MLIR-based infrastructure, and model-to-hardware optimization, with a strong focus on enabling high-performance execution for AI workloads. This role sits at the intersection of compiler development, ML frameworks, and AI model execution, supporting advanced acceleration pipelines targeting NPUs and other specialized compute engines.
Responsibilities
• Lead architecture design and development of compiler components and optimization pipelines for machine learning
• Design and implement MLIR-based compiler flows to lower high-level ML representations into highly optimized hardware-specific code
• Drive model compilation and data movement optimization for ML inference workloads
• Define and implement compiler strategies for operator fusion, memory planning, scheduling, and performance optimization
• Work cross-functionally with hardware, runtime, frontend, and systems teams to align compiler capabilities with evolving accelerator architectures
• Provide technical leadership and mentorship, influencing compiler direction and best practices across the organization
• Contribute to long-term roadmap decisions for compiler and ML acceleration software
Qualifications
Minimum
• Strong experience in compiler development (front-end, middle-end, and/or back-end) and code optimization
• Hands-on expertise with MLIR and/or LLVM-based compiler infrastructure
• Proven experience working on neural network workloads
• Deep understanding of graph-level and compiler-level optimizations for ML models
• Strong C++ development skills and experience working in large, complex codebases
• Ability to operate at Principal-level technical scope, influencing architecture and direction beyond individual deliverables
Preferred
• Experience targeting or optimizing for NPUs or specialized AI accelerators
• Familiarity with model compilation stacks and custom lowering pipelines
• Contributions to compiler or ML infrastructure in production environments