Software Engineering Manager, AI Compiler

Meta Platforms, Inc.
New York, NY, United States
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Working hours
Regular working hours
Job source

Tech stack

Mxnet Adobe InDesign Artificial Intelligence Compilers Code Generation Nvidia CUDA Computer Programming Microprocessors OpenMP OpenCL Tensorflow Software Engineering
+7 more
Graphics Processing Unit (GPU) Pytorch Parallel Computation ONNX (Open Neural Network Exchange) Format Machine Learning Operations Vectorization MLIR (Multi-Level Intermediate Representation)

Job description

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., * 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.

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., * 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.

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