Wendy Hu
Staff Software Engineer at Databricks
San Francisco Bay Area United States
Summary
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Rockstar🎓
Top SchoolWendy Hu is a Staff Software Engineer in the San Francisco Bay Area with 11 years of experience building ML infrastructure and model serving platforms. Currently focused on Foundation Model Serving at Databricks, she progressed through engineering roles there after earlier ML and infrastructure work at Quora and internships across Facebook, Wish, and Remind. Wendy has contributed to the widely used open-source MLflow project, improving model registry, multi-framework input support (Keras/PyTorch/TensorFlow), and scoring server features—work that bridges model development and production deployment. She combines hands-on systems engineering with practical ML deployment expertise, and her background in both product-facing services and low-level identity and data reliability work gives her a rare full-stack perspective on production ML systems.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Software Engineering (BSE) Software Engineering, Bachelor of Software Engineering (BSE) Software Engineering at University of Waterloo
Github Skills (18)
pytorch10
python10
machine-learning10
model-management10
mlflow10
keras10
tensorflow10
apidoc9
api9
rest-api9
documentation8
pandas8
dataframes8
dataframe8
json8
Programming languages (3)
Github contributions (5)
mlflow/mlflow
Dec 2020 - Oct 2022
Open source platform for the machine learning lifecycle
Role in this project:
ML Engineer
ML EngineerContributions:29 reviews, 13 commits, 20 PRs in 1 year 10 months
Contributions summary:Wendy primarily contributed to the core functionality of the MLflow platform, particularly focusing on model registry and deployment aspects. They implemented features related to creating and managing model versions, including optional parameters for run IDs. The user also added support for various input types, specifically for Keras, PyTorch, and TensorFlow models, and enhanced documentation on input handling. Further improvements were made to the scoring server, incorporating features like a version endpoint and support for TF Serving input formats.
pythonlifecyclemlmachine-learningincremental-learning
wentinghu/mlflow
Dec 2020 - Oct 2022
Open source platform for the machine learning lifecycle
Contributions:2 PRs, 97 pushes, 19 branches in 1 year 10 months
pythonlifecyclemachine-learningmodel-managementmachine-learning-lifecycle
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