Jason Wang
Software Engineer at Microsoft
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolJason Wang is an applied scientist with nine years of experience building machine learning, ranking, recommendation, and backend systems across Microsoft, News Break, Facebook, and Google Research. He combines rigorous academic training (Ph.D. in ECE) with hands-on engineering, shipping production ranking and news-core models at Microsoft and scalable ML-driven features at News Break. His background in video content understanding and research internships informs a strong foundation in model design and evaluation, while contributions to popular open-source projects like ONNXMLTools and SynapseML show expertise in model conversion, distributed ML, and production interoperability. Jason is comfortable bridging research and engineering—fixing tricky converter edge cases, improving SparkML-to-ONNX workflows, and hardening distributed model components—which helps teams move prototypes into reliable, maintainable systems. Based in Bellevue, he brings both deep technical breadth and a practical focus on shipping impactful ML systems.
10 years of coding experience
1 year of employment as a software developer
Bachelor of Science (B.S.), Computer Science, Bachelor of Science (B.S.), Computer Science at University of MichiganBachelor of Business Administration (B.B.A.), Bachelor of Business Administration (B.B.A.) at University of Michigan Business School
Chinese
Stackoverflow
494reputation
24kreached
22answers
0questions
Github Skills (19)
apache-spark10
python10
machine-learning10
cntk10
onnx10
scala10
scikit9
big-data9
scikit-learn9
ai9
azure8
microsoft-azure8
testing8
keras7
api6
Programming languages (11)
Github contributions (5)
microsoft/SynapseML
Jun 2021 - Sep 2022
Simple and Distributed Machine Learning Python Library porting ML algorithms for Spark
Role in this project:
Backend Developer & ML Engineer
Backend Developer & ML EngineerContributions:153 reviews, 33 commits, 40 PRs in 1 year 3 months
Contributions summary:Jason contributed to bug fixes and addressed build warnings within the codebase. A significant portion of their work focused on resolving issues related to the `CNTKModel` and `BingImageSearch` components, indicating involvement in model performance and cognitive service integration. They also made adjustments related to the `VowpalWabbitContextualBandit` and `EnsembleByKey` stages, demonstrating familiarity with distributed machine learning techniques and model ensembling.
machine-learningportingpythonsparkpyspark
onnx/onnxmltools
May 2022 - Jun 2022
ONNXMLTools enables conversion of models to ONNX
Role in this project:ML Engineer
ML EngineerContributions:8 reviews, 10 commits, 12 PRs in 1 month
Contributions summary:Jason focused on enhancing the ONNXMLTools library by adding support for various SparkML models to ONNX conversion. Their contributions involved implementing converters for SparkML's KMeansModel, VectorAssembler, CountVectorizer, StringIndexerModel, and MultilayerPerceptronClassifier, and fixing issues with existing converters like StandardScaler. They addressed issues related to handling vector inputs and ensuring compatibility, demonstrating expertise in machine learning model conversion and ONNX integration. The user's work also included updating unit tests and refining the conversion process for specific SparkML models.
onnxmachine-learningpython-libraryscikit-learnkeras
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