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Research Scientist Intern, PyTorch On-Device

United States, Bellevue 7650.00 - 12134.00 USD / Month · Job Posted February 16, 2026
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Job Description

PyTorch is Meta’s deep learning framework for fast, flexible AI/ML experimentation used across industry and backing all of Meta’s ML workloads. Our team brings PyTorch to edge devices through the use of compilers, an optimized runtime, and leveraging unique mobile hardware (CPU, GPU, NPU, DSP) for inference and training. Team scope: - Develop ExecuTorch as the PyTorch solution for on-device AI - Partner with Reality Labs to run AI on AR/VR hardware - Partner with Meta family of apps for running AI on iOS and Android - Partner with hardware vendors on high-performance AI kernels - Provide on-device AI inference, feature stores, benchmarking, and model delivery. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.

Job Responsibility

  • Develop new or apply existing performance techniques to on-device AI
  • Explore quantization, sparsity, and model/software co-design as solutions
  • Apply knowledge and research to advance the state-of-the-art in on-device machine learning frameworks
  • Collaborate with users and developers of PyTorch and ExecuTorch to enable new use cases inside and outside Meta

Requirements

  • Currently has, or is in the process of obtaining, PhD degree in the field of Computer Science or a related STEM field
  • Experience in ML compilers, sparsity, quantization, kernel development, or similar as applied to on-device and highly-constrained environments
  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Nice to have

  • Experience working on other AI/ML optimized runtime stacks
  • Experience with performance optimization of machine learning models for on-device inference
  • Intent to return to degree program after the completion of the internship/co-op
  • Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, MLSys, ASPLOS, PLDI, CGO, PACT, ICML, or similar
  • Experience working and communicating cross functionally in a team environment
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