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Meta Platforms - Austin, TX

posted 11 days ago

- Mid Level
Austin, TX
Broadcasting and Content Providers

About the position

Meta Reality Labs (RL) is the world leader in the design of virtual and augmented reality systems. Come work alongside expert engineers and research scientists to create the technology that makes VR and AR pervasive and universal. Join the adventure of a lifetime as we make science fiction real and change the world. 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. The successful candidate 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. The ideal candidate will contribute to a full stack development effort compiling PyTorch models down to binaries for hardware accelerator blocks.

Requirements

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
  • 3+ years experience writing compilers 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 crossing multi-disciplinary boundaries to drive optimal system solutions.
  • Experience in AI framework development or accelerating deep learning models on hardware architectures.
  • 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, Tensorflow or Caffe.
  • Experience working on and contributing to an active compiler toolchain codebase, such as LLVM, MLIR, GCC, MSVC, Glow.
  • Experience with machine-code generation or compiler back-ends.
  • Experience working and communicating cross functionally in a team environment.
  • Experience driving large efforts across multiple teams.
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