Software Engineer, Systems ML - Compilers / Backend

Meta•Sunnyvale, CA

21h•$121,992 - $181,000

About The Position

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.

Requirements

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

Nice To Haves

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, MLIR, Tensorflow or Caffe
1+ years experience developing compilers or similar code optimization software
Experience collaborating with hardware, firmware, or algorithm teams to define and deliver shared technical objectives
Experience developing high-performance kernels or runtime components and tuning them for inference specific accelerator platforms
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
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 with machine-code generation or compiler back-ends for on-device inference workloads
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

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