About the job
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. This position is focused on the graph-level optimizations, including graph partitioning and memory planning, that are needed to efficiently deploy models on a variety of edge devices.
Responsibilities
Contribute to the development of machine-learning libraries, intermediate representations, export formats, and analysis tools
Design and implement effective compiler passes and optimizations in PyTorch's intermediate representations
Analyze and improve the efficiency, scalability, and stability of our toolchains, and make sure they can be extended to new use cases
Generalize contributions to be applicable to as many devices as possible in the Reality Labs portfolio
Interface with other compiler-focused teams to evaluate and incorporate their innovations, including direct interactions with the PyTorch and ExecuTorch teams
Conduct design and code reviews. Evaluate code performance, debug, diagnose and drive resolution of compiler and cross-disciplinary system issues
Qualifications
Minimum
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
4+ 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 of developing in a mainstream machine-learning framework, e.g. PyTorch or TensorFlow
Preferred
PhD in Computer Science, Computer Engineering, or relevant technical field
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 with model co-design for custom silicon targets
Experience using ExecuTorch (or TFLM/LiteRT) for deployment, or contributing directly to any of the existing delegates
First author publications experience at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL)
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies