Tian Qin
Staff Machine Learning Engineer at TikTok
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolTian Qin is a Staff Machine Learning Engineer based in Sunnyvale with five years of industry experience building ML-driven monetization and ads systems at TikTok and foundational software work at Google and Amazon. Trained in computer science and computational data science at Peking University and Carnegie Mellon, Tian blends rigorous academic modeling with production engineering on large-scale ad and analytics products. He focuses on modernizing traditional ML tools and algorithms and brings low-level systems enthusiasm to his work, favoring Rust and C for performance-critical components. At TikTok he progressed from app monetization models to core ads architecture, and earlier roles included campaign and analytics systems at Google and pCTR and personalization efforts at Baidu. Known for connecting research-grade approaches (e.g., anomaly detection and forecasting from his research background) to deployable, auditable systems, he excels at turning complex data science into reliable production services.
5 years of coding experience
5 years of employment as a software developer
Bachelor of Arts (B.A.), Economics (Double Major), Bachelor of Arts (B.A.), Economics (Double Major) at Peking UniversityMaster's degree, Computational Data Science, Master's degree, Computational Data Science at Carnegie Mellon University
English, Chinese
Github Skills (73)
python10
forge10
feature-engineering10
apache-arrow10
polars10
threaded10
matrix10
dataframes10
panel-data10
code-editor10
rust10
dataframe10
game-engine9
statistics9
developer-tools9
Programming languages (7)
Github contributions (5)
abstractqqq/polars_ds_extension
Oct 2023 - Apr 2025
Polars extension for general data science use cases
Contributions:35 releases, 19 reviews, 465 PRs in 1 year 5 months
abstractqqq/polars_istr
Feb 2024 - Feb 2025
Identifiers and Standard Format Parsing for Polars Dataframe
Contributions:2 releases, 3 reviews, 19 PRs in 11 months
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