Jay Chia
Co-Founder at Eventual
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJay Chia is a Co-Founder and engineer based in San Francisco with 10 years of experience building large-scale data and ML infrastructure across biotech, autonomous vehicles, and computer vision pipelines. A Cornell CS graduate with a 3.99 GPA, he combines deep systems and distributed-systems expertise with hands-on backend development—contributing core abstractions and UDF support to the Rust-powered Daft distributed data engine. At Eventual he focuses on making visual-data ingestion and processing seamless for enterprise ML teams, translating production pain points into scalable pipeline and warehouse designs. Previous roles at Freenome and Lyft involved designing compute and data platforms that accelerated model development for high-stakes applications. His background ranges from iOS product work at Facebook to operational leadership as a tank platoon commander, which surfaces in pragmatic, mission-oriented engineering and team-building. He brings an unusual mix of applied ML infrastructure know-how, open-source contributions, and operational discipline to early-stage product and platform challenges.
10 years of coding experience
5 years of employment as a software developer
Y CombinatorBachelor's degree, Computer Science, 3.99, Bachelor's degree, Computer Science, 3.99 at Cornell University
Malay, Chinese, English
Stackoverflow
1reputation
740reached
0answers
1question
Github Skills (6)
data-structures10
python10
data-structure10
data-engineering9
flask-sqlalchemy6
sqlalchemy6
Programming languages (6)
Github contributions (5)
Eventual-Inc/Daft
Apr 2022 - Jan 2023
Distributed data engine for Python/SQL designed for the cloud, powered by Rust
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 releases, 917 reviews, 406 commits in 9 months
Contributions summary:Jay primarily contributed to the development of core data engine functionality within the daft project. Their work focused on implementing core abstractions for managing data repositories and adding functionality for defining and running operations on the data. They demonstrated a solid understanding of software design and data structures, by implementing features such as UDFs.
data-analysispythonpolarsdata-sciencedataframe
jaychia/ray
Apr 2023 - Mar 2025
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.
Contributions:24 pushes, 2 branches in 1 year 11 months
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