Research Engineer, Systems ML - Compilers - Reality Labs Silicon AI Team
Listed on 2026-02-28
-
Software Development
AI Engineer, Software Engineer, Machine Learning/ ML Engineer
Overview
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.
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 tool chains, 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 Execu Torch teams
Conduct design and code reviews. Evaluate code performance, debug, diagnose and drive resolution of compiler and cross-disciplinary system issues
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 Tensor Flow
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 Execu Torch (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)
Public Compensation: $88.46/hour to $257,000/year + bonus + equity + benefits
IndustryIndustry: Internet
Equal OpportunityEqual Opportunity: Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at
#J-18808-Ljbffr(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).