Paul Shao
Senior Software Engineer at Meta
United States
Summary
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Rockstar🎓
Top SchoolPaul Shao is a Senior Software Engineer at Meta with eight years of experience building scalable, user-focused features for Messenger and Instagram Direct, specializing in iOS contact, group chat, and search & discovery systems. A UC Berkeley EECS graduate (3.94 GPA), he blends strong academic foundations with hands-on ML and systems work—from low-level PyTorch kernel optimizations that cut training latency to backend services that parallelize and cache thousands of model runs. He has a consistent track record of shipping product-facing features that measurably boost engagement and performance, and has delivered full-stack solutions across React, Flask, Kubernetes, Redis, and mobile platforms. Paul contributes to language tooling and test automation in the P programming language repository, reflecting an interest in correctness and runtime behavior beyond typical application code. He’s comfortable moving between deep optimization and high-level UX problems, and often surfaces non-obvious wins by connecting systems design to measurable user impact.
8 years of coding experience
4 years of employment as a software developer
Bachelors, Electrical Engineering and Computer Science, GPA: 3.94/4.00, Bachelors, Electrical Engineering and Computer Science, GPA: 3.94/4.00 at UC Berkeley College of Engineering
Github Skills (8)
programming-language10
regression-testing10
formal-verification10
model-checking9
state-machine9
event-driven8
asynchronous8
distributed-systems7
Programming languages (9)
Github contributions (5)
p-org/P
Sep 2019 - Sep 2019
The P programming language.
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:9 commits, 3 PRs, 8 pushes in 7 days
Contributions summary:Paul primarily contributed to the development and testing of the P programming language. Their work included modifying core components, as evidenced by the changes to `PrtValues.c`, and implementing regression tests to ensure the correct behavior of the language's features, as seen in the modifications to the test files. Furthermore, the user appears to be involved in debugging and addressing errors within the test suite.
model-checkingcoq-librarytlaformal-verificationcompiler
paulshaoyuqiao/pytorch
May 2020 - Aug 2020
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Contributions:144 pushes, 30 branches in 2 months
pythongpu-accelerationdeep-learninggpuacceleration
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