Software Engineering Manager, AI Compiler

Meta - New York, NY

Full-time - Manager

New York, NY

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About the position

The MTIA (Meta Training & Inference Accelerator) Software team is at the forefront of developing a comprehensive AI Compiler strategy, focusing on optimizing compiler toolchains. This initiative is crucial for enabling the training and inference of Meta's production deep learning and machine learning workloads on specialized MTIA AI accelerator hardware. We are seeking a Software Engineering Manager who will lead the development of the compiler stack and drive high-performance compiler optimizations and tuning specifically tailored for the MTIA AI accelerator hardware. In this role, the Software Engineering Manager will be responsible for growing a team of domain experts within the AI Compiler space. This includes fostering a collaborative environment where communication and relationship-building with clients and peer teams are essential for facilitating cross-functional projects. The manager will operate both strategically and tactically, developing a clear vision and strategy while helping to set the direction for the team. Staying up-to-date with ongoing software development activities is critical, as the manager will assist in navigating technical challenges and will be involved in key design decisions that impact the team's output and effectiveness.

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, developing vision and strategy 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.

Requirements

• 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.

Nice-to-haves

• 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.