Bobak
Summary
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RockstarBobak Hashemi is a Senior Software Engineer specializing in machine learning at Meta, focusing on LLM training and evaluation to boost employee productivity. With a PhD-level physics background and three years in ML roles, he blends rigorous research experience from CERN and FAIR with production-grade engineering. He led development of torcheval, an open-source library for neural network evaluation, and has hands-on experience deploying efficient RNNs and MLOps pipelines in clinical settings. His work spans large-scale data systems, high-performance C++/Python tooling, and novel algorithm development for sensor tracking, reflecting a pattern of turning complex scientific problems into scalable software. Based in California, he brings both deep quantitative instincts and practical product delivery experience to ML infrastructure and model evaluation.
4 years of coding experience
Github Skills (19)
reinforcement-learning9
pytorch9
mujoco7
distributed-training7
simulation6
type-check6
type-checking5
ocaml5
reinforcement-learning-environments5
machine-learning5
python5
artificial-intelligence4
abstract-interpretation4
security4
deep-learning4
Programming languages (3)
Github contributions (5)
bobakfb/torcheval
Aug 2022 - Dec 2023
A library that contains a rich collection of performant PyTorch model metrics, a simple interface to create new metrics, a toolkit to facilitate metric computation in distributed training and tools for PyTorch model evaluations.
Contributions:2 PRs, 28 pushes, 28 branches in 1 year 4 months
pytorchcomputationcreate-newpytorch-modelevaluations
meta-pytorch/torcheval
Aug 2022 - Jan 2023
A library that contains a rich collection of performant PyTorch model metrics, a simple interface to create new metrics, a toolkit to facilitate metric computation in distributed training and tools for PyTorch model evaluations.
Contributions:1 release, 7 reviews, 28 commits in 5 months
distributed-trainingpytorch
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