Software Engineer, ML Compiler

Full-time - Mid Level

Sunnyvale, CA

5,001-10,000 employees

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About the position

Meta Reality Labs is seeking a software engineer to support the development of a compiler tool-chain for advanced deep learning hardware components optimized for augmented and virtual reality systems. The role involves architecting, designing, and implementing a new compiler, contributing to a full stack development effort that compiles PyTorch models into binaries for hardware accelerators. The successful candidate will work alongside a team of experts in compilers, machine learning algorithms, and hardware design to create innovative solutions in the AR/VR space.

Responsibilities

• 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 and 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 toolchains.
• Interface with other compiler-focused teams to evaluate and incorporate innovations.
• Mentor other engineers on improving the quality of engineering work.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience.
• 3+ years experience writing compilers or similar code optimization software.
• Experience in software design and programming 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.

Nice-to-haves

• Experience in deep learning algorithms and techniques, e.g., convolutional neural networks, recurrent networks.
• Experience 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.

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• 401k
• Paid holidays
• Paid volunteer time
• Flexible scheduling
• Professional development
• Employee discount programs