Kevin Tse - Product Manager at CircleCI

Kevin Tse

Product Manager at CircleCI

San Francisco Bay Area United States

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Summary

🤩

Rockstar

🎓

Top School

Kevin Tse is a product manager and former software engineer with 10 years of experience building ML-infused products and developer-facing systems from San Francisco. He’s led machine learning product efforts at Glassdoor and Snorkel AI and now drives product at CircleCI, combining technical fluency with go-to-market execution. Kevin’s hands-on engineering background includes meaningful open-source contributions to PyTorch—improving DataPipe behavior, CI integration for torchdata, and test automation—which informs pragmatic decisions around scalability and developer experience. He has a strong track record in HR tech, having boosted applicant volume and quality through AI-driven product features at eightfold.ai, and in shipping impactful full-stack migrations and analytics work at Prezi. Kevin holds an Information Science BA from Cornell and an MBA from Wharton, and outside work he blends interests in music and machine learning to explore novel product ideas. Notably, he often bridges MLOps, QA, and product strategy to turn complex ML infrastructure problems into usable customer outcomes.

10 years of coding experience

9 years of employment as a software developer

B.A Information Science, B.A Information Science at Cornell University

Master of Business Administration (MBA) Entrepreneurial Management/Business Analaytics, Master of Business Administration (MBA) Entrepreneurial Management/Business Analaytics at The Wharton School

Chinese

Github Skills (25)

unit-testing10

pytorch10

pytest10

python10

machine-learning10

datasets10

deep-learning10

test-automation10

data-engineering9

debug9

debugging9

cicd9

ml9

devops9

mle9

Programming languages (6)

MDXJavaC++HTMLJupyter NotebookPython

Github contributions (5)

pytorch/data

Sep 2021 - Jan 2023

A PyTorch repo for data loading and utilities to be shared by the PyTorch domain libraries.

Role in this project:

QA Engineer / Test Automation Engineer

Contributions:790 reviews, 471 commits, 251 PRs in 1 year 4 months

Contributions summary:Kevin's commits primarily focused on enhancing the testing framework within the repository. The commits introduced a "slowTest" for tests that require file downloads and changed the testing framework to use `unittest.main()`. The user also ensured the tests can handle consistent file reading and fixed an issue related to closing streams in the archive reader.

pytorchpythondeep-learningtorchmachine-learning

pytorch/pytorch

Jun 2021 - Nov 2022

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Role in this project:

Back-end Developer

Contributions:484 reviews, 492 commits, 150 PRs in 1 year 5 months

Contributions summary:Kevin primarily contributed to the PyTorch codebase by addressing issues related to the DataPipe functionality. Their work included minor documentation improvements, fixing an unraised exception within the event loop, implementing lazy generation of exception messages for performance reasons, and disabling the profiler for IterDataPipe by default. Furthermore, they added a function for deprecation of functional DataPipe names, corrected error messages, and refactored iterator-related code for better readability and performance.

pythongpu-accelerationdeep-learninggpunumpy

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