Research Engineer, Systems ML - Compilers - Reality Labs Silicon AI Team

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
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 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