Avik Chaudhuri
Software Engineer at Meta
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolAvik Chaudhuri is a seasoned software engineer with 12 years of experience in programming languages, compilers, and machine learning infrastructure, currently tackling hard technical problems at Meta in the San Francisco Bay Area. He has led technical efforts for Flow (a fast, precise JS type checker) and now provides technical leadership for PyTorch Export, an AOT compiler for PyTorch models. His work spans deep systems-level contributions—optimizing type checkers and static analyses—to ML-facing compiler and export tooling, and he’s an active open-source contributor to high-profile projects like React Native and PyTorch. Unusually for someone at this scale, he blends research pedigree (PhD-level program analysis and security work) with day-to-day engineering, including concrete patches improving UI components and dynamic-shape semantics.
12 years of coding experience
19 years of employment as a software developer
Indian Institute of Technology Delhi (IIT Delhi)University of California Santa Cruz
English, Spanish, French
Stackoverflow
235reputation
11kreached
7answers
0questions
Github Skills (39)
pytorch10
serializable10
javascript10
parser10
mobile-development10
react-native10
serializer10
python10
typescript10
machine-learning10
serialization10
deserialization10
type-system10
parsing10
optmization10
Programming languages (8)
Github contributions (5)
facebook/flow
Nov 2014 - Oct 2019
Adds static typing to JavaScript to improve developer productivity and code quality.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:841 commits, 8 PRs, 36 pushes in 4 years 11 months
Contributions summary:Avik was actively involved in maintaining and developing the Flow type checker, with a focus on optimization and bug fixes. They made numerous code changes to enhance the performance and efficiency of the type checker, including optimizations for processing specific language features, as well as significant refactorings to code structure to improve maintainability. The user also contributed to the testing suite, addressing bugs.
static-typingproductivityjavascriptdeveloper-productivitydataflow-programming
pytorch/pytorch
Jan 2023 - Jan 2023
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:636 reviews, 51 commits, 201 PRs in 10 days
Contributions summary:Avik contributed to the PyTorch library, focusing on improvements to its shape environment, constraint solver, and export functionality. The user's work included fixing data-dependent errors, enhancing the dynamic shape specification API, and addressing issues related to unflattening and serialization. The user's contributions demonstrate their expertise in the internal workings of PyTorch and their focus on enhancing the library's features related to dynamic shapes, constraints, and the export module.
pythongpu-accelerationdeep-learninggpunumpy
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