Taehee Jeong
Senior Software Engineer at Waymo
California, United States
Summary
🤩
Rockstar🎓
Top SchoolTaehee Jeong is a Senior Software Engineer based in California with 11 years of experience building mobile and edge ML systems, currently at Waymo after several roles at Google. He specializes in TensorFlow Lite, model optimization (quantization/pruning), and hardware acceleration on iOS—contributing notable improvements like a Core ML delegate for PoseNet to run on the Neural Engine. Taehee blends a formal CS education with a life sciences minor and early neuroscience research, reflecting a long-standing curiosity about intelligence in both machines and biology. His background includes hands-on IoT edge work and published neuroanatomy research, an uncommon mix that informs pragmatic, performance-driven ML engineering. An active open-source contributor, he maintains practical tooling and build fixes in the TensorFlow ecosystem while shipping production-ready mobile ML features.
11 years of coding experience
9 years of employment as a software developer
학사 컴퓨터 공학, 학사 컴퓨터 공학 at Seoul National UniversityHigh school, High school at Korea Science Academy of KAIST
Korean, English
Stackoverflow
146reputation
10kreached
26answers
0questions
Github Skills (20)
ios10
python10
machine-learning10
coreml10
model-compression10
keras10
tensorflow10
swift10
optimization10
mobile-development9
pruning9
quantization9
deep-learning8
deeplearning-ai8
bazel7
Programming languages (6)
Github contributions (5)
tensorflow/model-optimization
Nov 2020 - Apr 2021
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
Role in this project:
ML Engineer
ML EngineerContributions:16 commits, 1 PR, 1 push in 5 months
Contributions summary:Taehee primarily contributed to the maintenance and improvement of the TensorFlow Model Optimization toolkit. Their work involved fixing dependencies, updating build configurations, and refactoring code. Specific contributions include updating the implementation of the strict build rules, dependency fixes for various Python modules, and some formatting adjustments.
ml-modelspythonquantized-networkstensorflowsparsity
tensorflow/examples
Apr 2020 - Apr 2021
TensorFlow examples
Role in this project:Mobile Developer (iOS)
Mobile Developer (iOS)Contributions:8 commits in 1 year
Contributions summary:Taehee primarily contributed to the PoseNet iOS example within the TensorFlow project. Their work involved adding and refining features like the Core ML delegate for hardware acceleration, allowing the model to run on the device's Neural Engine. The user also made changes related to thread count management and deprecated API updates within the iOS app's codebase. These modifications aimed to improve the app's performance and compatibility with the TensorFlow Lite framework.
tensorflow
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