Yunhui Zhang
Technical Lead at Yelp
Montreal, Quebec, Canada
Summary
🤩
Rockstar🎓
Top SchoolYunhui Zhang is a Technical Lead in Montreal with 10 years of experience building production ML platforms and leading engineering teams across startups and large enterprises. At Yelp he drives the ML platform roadmap, partners with internal teams to streamline model development and deployment, and oversees technical projects that enable business initiatives. Previously he architected AutoML pipelines on Argo and refactored in-house ML libraries at Stradigi AI, and earlier built embedded and telecom software as a chief architect at ZTE and GDNT. An active contributor to MLeap, he improved TensorFlow 2.0 integration and robust tensor round-trip testing—demonstrating a mix of low-level systems rigor and production ML deployment expertise. Fluent in translating research into reliable production systems, he combines deep C++/embedded background with modern cloud-native ML engineering.
10 years of coding experience
11 years of employment as a software developer
Computer, Computer at South China University of Technology
Stackoverflow
1reputation
22reached
1answer
1question
Github Skills (13)
tensorflow10
scala10
data-pipelines9
data-pipeline9
machine-learning9
javas8
test-automation8
java8
ivy6
amazon-sagemaker6
deep-learning6
ant6
tensorflow-datasets6
Programming languages (8)
Github contributions (5)
combust/mleap
May 2021 - Dec 2022
MLeap: Deploy ML Pipelines to Production
Role in this project:
ML Engineer
ML EngineerContributions:2 releases, 31 reviews, 19 commits in 1 year 7 months
Contributions summary:Yunhui primarily contributed to improving the integration between the MLeap deployment framework and TensorFlow. Their work involved adding support for TensorFlow 2.0 and the new tensorflow/java binding, replacing older dependencies. They also focused on ensuring correct conversion and round-trip testing between MLeap tensors and TensorFlow tensors, covering various data types. Furthermore, they added new test cases and demonstrated the bug related to tensor get method.
transformerspythonml-pipelinesmleapdata-science
austinzh/mleap
Jun 2021 - Nov 2024
MLeap: Deploy ML Pipelines to Production
Contributions:40 pushes, 9 branches in 3 years 5 months
pythonml-pipelinesmleapdata-scienceml
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