Parmeet Bhatia is a Machine Learning Software Engineer with 8 years of experience building production-grade ML systems, currently contributing to Meta’s AI Platform for PyTorch. He has a strong track record of taking deep learning research into productized solutions, notably leading cross-functional teams at Siemens Healthineers to automate radiology and MR scanner workflows. Comfortable across the stack, he focuses on scalable data handling and model deployment while also improving developer experience—evident from contributions to the widely used pytorch/text library around data loaders and dataset docs. His background blends academic rigor from EPFL and IIT Roorkee with applied R&D, including open-source clustering tools developed at INRIA. Known for bridging research and engineering, he often surfaces practical fixes that simplify adoption and maintenance of ML tooling.
8 years of coding experience
9 years of employment as a software developer
Indian Institute of Technology Roorkee
Master of Science, Electrical engineering, Master of Science, Electrical engineering at Ecole polytechnique fédérale de Lausanne
Models, data loaders and abstractions for language processing, powered by PyTorch
Role in this project:
Back-end Developer
Contributions:2 releases, 390 reviews, 220 commits in 1 year 5 months
Contributions summary:Parmeet primarily focused on documentation improvements and bug fixes related to data loading and text classification datasets within the PyTorch text processing library. They addressed issues with the documentation of text classification datasets and improved the usability of existing datasets. These changes indicate a focus on data handling and streamlining the user experience of the library.
Contributions:502 pushes, 313 branches in 1 year 5 months
nlpabstractionsnatural-language-processingloaders
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Parmeet Bhatia - Software Engineer, Machine Learning at Meta