David Liu
Software Engineer at Chalk
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolDavid Liu is a pragmatic software engineer and GT computer science master’s candidate with a decade of engineering experience building low-latency, production-ready systems across Python, Java, C++, Rust, Go, and TypeScript. He has driven query planning and feature-store infrastructure at Chalk, delivered reliability and performance improvements for Amazon’s fulfillment services, and built LLM-powered automation that cut on-call load in half. His background spans applied ML and HCI research—shipping forum sentiment and counterargument prototypes and hybrid extractive-abstractive summarization work—plus hands-on fintech automation that increased straight-through processing by 5%. A disciplined tester and QA-minded contributor, he’s improved edge cases in open-source projects like sportsipy and consistently strengthens CI, serialization, and cross-language integrations. Based in New York, he blends systems thinking with curiosity about human-facing data insights, and will complete his MS in Spring 2025.
10 years of coding experience
4 years of employment as a software developer
High School Diploma, HIGH SCHOOL/SECONDARY DIPLOMAS AND CERTIFICATES, High School Diploma, HIGH SCHOOL/SECONDARY DIPLOMAS AND CERTIFICATES at North Carolina School of Science and MathematicsDual Enrollment, Mathematics, Dual Enrollment, Mathematics at North Carolina State UniversityMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at Georgia Institute of TechnologyHIGH SCHOOL/SECONDARY DIPLOMAS AND CERTIFICATES, HIGH SCHOOL/SECONDARY DIPLOMAS AND CERTIFICATES at Enloe High School
English, Chinese
Github Skills (4)
pytest10
python10
testing10
statistics8
Programming languages (7)
Github contributions (5)
roclark/sportsipy
Nov 2019 - Nov 2019
A free sports API written for python
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:6 commits, 2 PRs, 6 comments in 8 days
Contributions summary:David focused on improving the reliability of the `sportsipy` library, specifically in the area of NFL game result calculations. They added unit tests to cover scenarios of ties and unplayed games, ensuring accurate reporting. Additionally, the user modified existing tests, changing assertions to use the `is` operator and updated the description of the `result` method. This work demonstrates a commitment to testing and validating the library's functionality.
pythonsports-referencesportsreferencestatistics
DavidLiuGit/GTAV_SupportHeli
Jan 2020 - Jan 2022
Contributions:14 releases, 186 commits, 82 pushes in 2 years
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