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.
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 support the co-design of hardware features mapping ML graphs to hardware implementations, modeling data-flows, creating cost-benefit analysis and estimating silicon power and performance
- Work with hardware architects to co-design hardware features that maximize performance, power efficiency and programmability
- Contribute to the development of machine-learning libraries, intermediate representations, export formats, and analysis tools
- Collaborate with the team to enhance the efficiency, scalability, and stability of our toolchains by focusing on kernel optimization and tuning
- Conduct design and code reviews. Evaluate code performance, debug, diagnose and drive resolution of compiler and cross-disciplinary system issues
- Interface with other compiler-focused teams to evaluate and incorporate their innovations and vice versa
Qualifications
- 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
- 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 (GPU, TPU, custom AI ASICs)
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment Experience working and communicating cross functionally in a team environment
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- 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
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Experience working on and contributing to an active compiler toolchain codebase, such as LLVM, MLIR, GCC, MSVC, Glow
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- 1+ years of experience developing compilers or similar code optimization software
- Experience with machine-code generation or compiler back-ends for on-device inference workloads
- Experience developing high-performance kernels or runtime components and tuning them for inference specific accelerator platforms