Software Engineering Manager, AI Compiler - Meta

The MTIA (Meta Training & Inference Accelerator) Software team has been developing a comprehensive AI Compiler strategy and optimizing compiler toolchains. This enables training and inference of Meta’s production DL/ML workloads on the specialized MTIA AI accelerator hardware in a highly performant and flexible way.We are looking for a Software Engineering Manager who drives the compiler stack development & high performance compilers optimizations and tuning, specific to the MTIA AI accelerator hardware.

RESPONSIBILITIES

Software Engineering Manager, AI Compiler Responsibilities:

• Grow a team of domain experts within AI Compiler.
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
• Operate strategically and tactically. Develop vision, strategy and help set direction for the team.
• Remain up-to-date on ongoing software development activities in the team, help work through technical challenges, and be involved in design decisions.

MINIMUM QUALIFICATIONS

Minimum Qualifications:

• Experience with compiler architecture and development, particularly ML compilers or DSLs or static/dynamic languages compilers.
• 2+ years of experience in managing a team of compiler engineers of varied skill levels.
• Experience with cross functional collaboration with hardware or AI framework teams.
• Demonstrated experience recruiting, building, structuring, leading technical organizations, including performance management.

PREFERRED QUALIFICATIONS

Preferred Qualifications:

• Experience with compiler optimizations such as loop optimizations, vectorization, parallelization, HW architecture specific optimizations.
• Experience in compiling and code generation targeting ML accelerators or custom hardware, GPUs or CPUs.
• Experience with different programming models for high-performance computations, e.g. GPU CUDA programming or OpenCL or OpenMP programming.
• Experience with MLIR, or LLVM or IREE or XLA or Triton or TVM or Halide.
• Knowledge of ML frameworks like PyTorch, TensorFlow, ONNX, MXNet, etc.