Software Engineer, Systems ML - Compilers

Meta Platforms, Inc.-posted about 1 month ago
Full-time • Mid Level
Redmond, WA
5,001-10,000 employees
Broadcasting and Content Providers
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We are seeking a software engineer to support the development of the compiler tool-chain for state-of-the-art deep learning hardware components optimized for AR/VR systems. You will be part of our efforts to architect, design and implement a clean slate compiler for this activity and will be part of a team that includes compiler, machine learning algorithms and software, firmware and ASIC experts. You will contribute to a full stack development effort compiling PyTorch models down to binaries for custom hardware accelerator blocks.

  • Analyze and design effective compiler passes and optimizations. Implement and/or enhance code generation targeting machine learning accelerators
  • Work with algorithm research teams to map ML graphs to hardware implementations, model data-flows, create cost-benefit analysis and estimate silicon power and performance
  • Contribute to the development of machine-learning libraries, intermediate representations, export formats, and analysis tools
  • Conduct design and code reviews. Evaluate code performance, debug, diagnose and drive resolution of compiler and cross-disciplinary system issues
  • Analyze and improve the efficiency, scalability, and stability of our toolchains
  • Interface with other compiler-focused teams to evaluate and incorporate their innovations and vice versa
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 2+ years experience developing compilers, runtime, or similar code optimization software
  • Experience in software design and programming experience in Python and/or C/C++ for development, debugging, testing and performance analysis
  • Experience in AI framework development or accelerating models on hardware architectures
  • Experience working and communicating cross functionally in a team environment.
  • Experience with machine-code generation or compiler back-ends.
  • Experience working on and contributing to an active compiler toolchain codebase, such as LLVM, MLIR, GCC, MSVC, Glow.
  • Experience in deep learning algorithms and techniques, e.g., convolutional neural networks, recurrent networks, etc.
  • Experience of developing in a mainstream machine-learning framework, e.g. PyTorch, MLIR, Tensorflow or Caffe.
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