Gang Cheng
Machine Learning Engineer at Bloomberg
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolGang Cheng is a machine learning engineer with nine years of industry experience and a current MS candidate in Computer Science at the University at Buffalo, focused on building large-scale recommendation and search systems. He has shipped production ML pipelines and embedding-based retrieval frameworks that served hundreds of millions of users at Weibo and Qutoutiao, and has applied transformer-based NLP to low-latency economic indicator extraction and news summarization at Bloomberg. His background spans end-to-end systems—modeling, feature engineering, Spark/PySpark pipelines, and deployment on AWS/Kubernetes—using Python, Go, Java, and Scala. Notably, he has implemented GCNs on graphs with billions of edges and two-tower retrieval architectures to optimize candidate generation at scale. Based in New York, he blends research experience from Apple’s search science team with hands-on infrastructure work to deliver robust, production-ready ML solutions.
9 years of coding experience
6 years of employment as a software developer
Bachelor of Science - BS, Applied Statistics, Bachelor of Science - BS, Applied Statistics at Shanghai University of International Business and EconomicsMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at University at Buffalo
Github Skills (36)
python10
machine-learning10
data-management10
clearml10
deep-learning10
aws10
gpu10
ai10
version-control10
experiment10
trains10
experiment-manager10
devops10
k8s10
numpy9
Programming languages (3)
Github contributions (5)
chengzegang/SIFT-in-PyTorch
Oct 2022 - Jan 2023
Contributions:2 releases, 21 commits, 19 pushes in 3 months
chengzegang/ROSup
Apr 2023 - Apr 2023
Nolife ROS needs some fun things happening.
Contributions:7 releases, 8 PRs, 82 pushes in 14 days
guipython3rosxbox-controller
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