Software Engineer, Systems ML - PyTorch Compiler, PyTorch Framework, PyTorch Performance

Software Engineer, Systems ML - PyTorch Compiler, PyTorch Framework, PyTorch Performance

This role is about developing the core PyTorch 2.0 technologies, innovating and advancing the state-of-the-art of ML compilers, and accelerating PT2 adoption through direct engagements with OSS and industry users. The PyTorch Compiler team is dedicated to making PyTorch run faster and more resource-efficient without sacrificing its flexibility and ease of use. The team is the driving force behind PT2, a step function change in PyTorch's history that brought compiler technologies to the core of PyTorch. PT2 technologies have gained industry-wide recognition since their first release in March 2023. The team is committed to building the PT2 compiler that withstands the test of time while striving to become the #1 ML framework compiler in the industry. The team is highly innovative, passionate about the technologies we build, and love to do technical work. Our work is open source, cutting-edge, and industry leading.

Responsibilities

Develop the PT2 compiler (e.g., TorchDynamo, TorchInductor, Export, PyTorch Core)

Improve PyTorch performance via systematic solutions for the entire community

Explore the intersection of the PyTorch compiler and PyTorch distributed

Optimize Generative AI models across the stack (pre-training, fine-tuning, and inference)

Collaborate with users of PyTorch to enable new use cases of PT2 technologies both inside and outside Meta

Minimum Qualifications

Advanced in Python or C++ programming

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

4+ years of research or industry experience in developing compilers, ML systems, ML accelerators, GPU performance, and similar

Preferred Qualifications

Experience in developing PyTorch / PT2, Triton, MLIR, JAX, XLA, TVM is a huge plus

Knowledge in GPU architecture, ML accelerator performance, and developing high-performance kernels

Experience in building OSS communities and extensive social media presence in the ML Sys domain

Experience with training models, end-to-end model optimizations, or applying ML to systems

Knowledge of communication collectives, PyTorch distributed, and parallelism

Experience in developing inside other ML frameworks like Caffe2, TensorFlow, ONNX, TensorRT

$85.10 / hour to $251,000 / year + bonus + equity + benefits

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