系统机器学习编译器软件工程师

Meta（Meta Platforms）岗位：Software Engineer, Systems ML - Compilers / Backend 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 map ML graphs to hardware implementations, model data-flows, create cost-benefit analysis and estimate 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

Analyze and improve the efficiency, scalability, and stability of our toolchains. Optimize and tune kernels and compiled code to achieve latency targets for ML inference

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

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

2+ years experience developing compilers, toolchains, 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 (GPU, TPU, custom AI ASICs)

Experience of developing in a mainstream machine-learning framework, e.g. PyTorch, MLIR, Tensorflow or Caffe

Experience with machine-code generation or compiler back-ends for on-device inference workloads

Experience working on and contributing to an active compiler toolchain codebase, such as LLVM, MLIR, GCC, MSVC, Glow

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

Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

Experience developing high-performance kernels or runtime components and tuning them for inference specific accelerator platforms

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In addition to base compensation, Meta offers benefits.

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Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

2+ years experience developing compilers, toolchains, runtime, or similar code optimization software.