Taejin Chun
Senior Software Engineer at Meta
Mountain View, California, United States
Summary
👤
Senior🎓
Top SchoolTaejin Chun is a Senior Software Engineer based in Mountain View with 10 years of experience building production AI and deep learning systems, currently working on Ads recommendation at Meta. He has a strong ML engineering background spanning computer vision, time-series forecasting, and NLP from roles at SAP, Arimo, and startups, and he helped launch the open-source "Human First AI" framework. Taejin combines research-caliber education (MS from Carnegie Mellon) with hands-on product delivery—shipping TensorFlow-based APIs, model ensembles, and hyperparameter tuning improvements in open-source projects. He frequently bridges product and technical roles, having served as Data Scientist and Product Manager, and brings practical experience deploying models at scale for cloud APIs and real-world services. An unspoken strength is his cross-disciplinary early career work in financial embedded systems and multilingual market expansion, which informs a pragmatic, systems-oriented approach to ML productization.
10 years of coding experience
9 years of employment as a software developer
Business Administration, Business Administration at 國立政治大學B.E., Electrical Engineering, GPA: 3.86/4.00, B.E., Electrical Engineering, GPA: 3.86/4.00 at 고려대학교Master of Science (MS), Electrical and Computer Engineering, 3.84/4.00, Master of Science (MS), Electrical and Computer Engineering, 3.84/4.00 at Carnegie Mellon University
Korean, Chinese, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (6)
machine-learning10
ensembles10
python10
documentation9
automl7
time-series5
Programming languages (5)
Github contributions (5)
h1st-ai/h1st
Aug 2020 - Sep 2022
Power Tools for AI Engineers With Deadlines
Role in this project:
ML Engineer
ML EngineerContributions:43 reviews, 161 commits, 35 PRs in 2 years
Contributions summary:Taejin's commits focused on enhancing the `StackEnsemble` class by adding docstrings to the `__init__` function, which clarifies the usage of input and output keys for submodels. Further contributions involved merging a development branch related to a demonstration project, suggesting work related to the AutoCyber example and also fixing the hyperparameter tuner class. This indicates the user's role in developing and refining machine learning ensemble models for the project and managing its related components.
predictive-maintenancecollaborationhome-automationpower-toolsdatascience-environment
TgithubJ/h1st
Aug 2020 - Sep 2020
Human-First AI solves the “cold-start” problem of Industrial AI: encoding human expertise to augment the lack of data, while bridging to powerful ML—based on experience building AI solutions at Panasonic: robotics predictive maintenance, cold-chain energy optimization, Gigafactory battery mfg, avionics, automotive cybersecurity, and more.
Contributions:5 pushes, 3 branches in 6 days
pythonbatterypredictive-maintenancecoldchain
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