Gengcong Yang
Machine Learning Engineer at Uber
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolGengcong Yang is a Machine Learning Engineer based in the Bay Area with a decade of experience and 2+ years in industry roles at ByteDance and Uber, plus deep research credentials including a first-author CVPR paper. He combines full-stack ML expertise—from problem formulation and large-scale model training to production deployment and observability for pricing systems—and has shipped quantized, low-latency vision models and large e-commerce retrieval pipelines handling millions of classes. His background spans top-tier research labs and industry, contributing to supercomputer-backed DL infrastructure at TACC and practical recall improvements at Tencent that translated into measurable business gains. Comfortable implementing low-level CUDA/C++ components as well as scalable production pipelines, he uniquely bridges research rigor with operational impact.
10 years of coding experience
3 years of employment as a software developer
Exchange Student, Computer Science, Exchange Student, Computer Science at National Chiao Tung UniversityMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at The University of Texas at AustinBachelor of Engineering - BE, Software Engineering, Bachelor of Engineering - BE, Software Engineering at Sun Yat-sen UniversityMaster of Engineering - MEng, Information Engineering, Master of Engineering - MEng, Information Engineering at Tsinghua University
Github Skills (22)
protein-structure8
memory-efficient7
pytorch6
gpu5
api5
restful-api4
machine-learning4
deep-learning4
restful4
rest4
python4
rest-api4
android3
optical-flow3
tensorflow3
Programming languages (2)
Github contributions (5)
controny/automatic-grasping
Apr 2018 - Jul 2018
A deep learning project
Contributions:51 commits, 1 PR, 17 pushes in 2 months
learning-projectpythondeep-learningmachine-learningtensorflow
controny/compiler-for-P
Jan 2018 - Oct 2023
Contributions:6 pushes in 5 years 10 months
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