Software Engineer, ML Compiler

In this position, you would support development of a 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 research, architect, design and implement a compiler and runtime stack, which compiles PyTorch models down to binaries for hardware accelerator blocks. You will be part of a team that includes compiler, machine learning algorithms and software, firmware and ASIC experts.

Software Engineer, ML Compiler Responsibilities

• Analyze and design effective compiler passes and optimizations. Research, implement, and/or enhance code generation targeting machine learning accelerators.


• Investigate new techniques 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.

Minimum Qualifications

• 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 deep learning models on hardware architectures.


• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.


• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred Qualifications

• 1+ years experience writing compilers or similar code optimization software.


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


• Experience working on and contributing to an active compiler toolchain codebase, such as LLVM, MLIR, GCC, MSVC, Glow.


• Experience of developing in a mainstream machine-learning framework, e.g. PyTorch, Tensorflow or Caffe.


• Experience with machine-code generation/compiler back-ends.


• Experience working and communicating cross functionally in a team environment.

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