Job description

You will be a member of the Inference Enablement Team and part of the bigger PyTorch AI framework organization. We build the foundational technology and frameworks that enable and optimize state-of-the-art model architectures on new hardware. We work with many different types of model architectures across Ads, Reels, Feed, Marketplace, IG, and GenAI. We support the enablement of models on all kinds of hardware as well, including CPU, GPU, and custom Silicon. We build the model publishing frameworks and platforms to accomplish this at scale for a large, broad set of models that are pushing the state of the art in Inference. Our work involves a blend of software systems and ML, and you'll have the opportunity to learn about how PyTorch works at a more in-depth level as well. We play an integral role in helping Meta ship the most important, state-of-the-art models for inference, including models with significant Ads Revenue gain, Reels Watch Time gain, all while saving multiple MegaWatts of power through our efficiency work. Development of software stack with one of the following core focus areas: AI frameworks, compiler stack, high performance kernel development and acceleration onto next generation of AI Accelerators architectures Contribute to the development of the PyTorch AI framework core compilers to support new state of the art inference and training AI hardware accelerators and optimize their performance Analyze neural networks, develop & implement compiler optimization algorithms Accelerate the next generation of deep learning models such as Recommendation systems, Generative AI, Computer vision, NLP etc Performance tuning and optimizations of deep learning framework & software components 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 Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Python and C/C++ programming skills Experience in AI framework development or accelerating deep learning models on hardware architectures Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) OR AI Compiler: Experience with compiler optimizations such as loop optimizations, vectorization, parallelization, hardware specific optimizations such as SIMD. Experience with MLIR, LLVM, IREE, XLA, TVM, Halide is a plus Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience working with kernel frameworks like Triton, or CUDA OR AI frameworks: Experience in developing training and inference framework components. Experience in system performance optimizations such as runtime analysis of latency, memory bandwidth, I/O access, compute utilization analysis and associated tooling development Knowledge of GPU, CPU, or AI hardware accelerator architectures Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

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aimlpython

Platform: meta
Effort: medium

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