Mike Ruberry
Distinguished Software Engineer at NVIDIA
Westmont, Illinois, United States
Summary
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Rockstar🎓
Top SchoolMike Ruberry is a Distinguished Software Engineer with eight years of focused experience in deep learning systems and ML infrastructure, currently leading advanced work at NVIDIA after principal research engineering at Lightning AI and prior engineering roles at Meta. He blends rigorous academic training from Harvard (PhD candidate in CS) and Yale (BS/MS) with hands-on contributions to high-impact open-source projects like PyTorch/XLA, where he strengthened test automation and device support for TPUs. Known for shipping robust test frameworks and precision-sensitive integrations, he moves research-grade models toward production-readiness and scalable GPU/TPU deployments. Based in Westmont, Illinois, he brings a rare mix of research pedigree and production engineering that accelerates ML platform reliability and developer velocity.
8 years of coding experience
8 years of employment as a software developer
PhD Computer Science, PhD Computer Science at Harvard UniversityBachelors and Masters of Science Computer Science, Bachelors and Masters of Science Computer Science at Yale University
Github Skills (9)
xla10
pytorch10
test-framework10
python10
test-automation10
testing10
deep-learning8
compiler-compiler8
compiler8
Programming languages (6)
Github contributions (5)
pytorch/xla
Sep 2019 - Feb 2020
Enabling PyTorch on XLA Devices (e.g. Google TPU)
Role in this project:
ML Engineer & QA Engineer / Test Automation Engineer
ML Engineer & QA Engineer / Test Automation EngineerContributions:4 reviews, 40 commits, 60 PRs in 4 months
Contributions summary:Mike primarily focused on enhancing the testing framework for PyTorch/XLA, specifically targeting XLA device support. Their contributions included adding XLA to device type testing, filtering tests, and integrating torch xla tests. They modified existing test files and created new test metadata, effectively expanding the testing coverage and ensuring the correct functionality of PyTorch on XLA devices. The user also excluded several tests and set floating-point precision.
pytorchxladeep-learningtpucompiler
mruberry/pytorch
Sep 2019 - Dec 2019
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Contributions:4 commits, 1 PR, 212 pushes in 2 months
pythongpu-accelerationdeep-learninggpuacceleration
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