Principal Software Engineer - AI Compiler Engineer
Role details
Job location
Tech stack
Job description
We are hiring a Principal Software Engineer to drive technical leadership across AMD's nextgeneration NPU compiler stack. This role requires deep expertise in compiler design, hardwareaware software optimization, and performance engineering. You will architect and implement key components of our MLIR/LLVMbased compiler stack, contribute novel fusion and optimization strategies, and lead technical direction across teams. Key Responsibilities
- Provide technical leadership for the architecture and development of AMD's NPU compiler stack.
- Design advanced IR transformations, graphlevel optimizations, and hardwareaware fusion passes.
- Guide system-wide performance strategies using deep knowledge of HW architecture constraints (memory, parallelism, dataflows).
- Collaborate with hardware architects, runtime teams, and ML framework teams (ONNX, PyTorch) to drive codesign.
- Drive performance investigations, benchmarking, and softwarehardware cooptimization.
- Represent AMD externally through technical publications, opensource contributions, or industry engagement.
- Mentor MTS/SMTS engineers and set technical direction for large compiler initiatives., AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's "Responsible AI Policy" is available here.
Requirements
- 12+ years of experience in compilers, performance engineering, or system-level software.
- Strong C++ expertise and proficiency in Python.
- Extensive hands-on experience with LLVM and MLIR.
- Experience designing optimizations tightly coupled to hardware architectures (e.g., tensor accelerators, GPUs, NPUs).
- Deep understanding of compiler internals: IR design, scheduling, memory optimizations, multi-stage lowering.
- Demonstrated experience delivering production-quality compiler or systems software.
- Experience driving technical strategy across teams and influencing product roadmaps.
Preferred Qualifications
- Contributions to opensource compiler/ML communities (LLVM, MLIR, XLA, TVM, Triton).
- Experience with AI/ML model execution, graph optimization, and performance tuning.
- Experience with domain-specific languages or IRs for machine learning.
- Knowledge of NPU/GPU execution models, memory hierarchies, and parallelism strategies.
Education
B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or related field
Benefits & conditions
$226,400.00/Yr.-$339,600.00/Yr.