Jay Zhang
Product Manager at DoorDash
Greater Seattle Area United States
Summary
🤩
Rockstar🎓
Top SchoolJay Zhang is a product and program leader with 8+ years driving finance-critical platforms at companies like DoorDash, Stripe, and Microsoft, specializing in automated financial reporting, reconciliation, and billing for both B2B and B2C commerce. He blends big-data and cloud-native architectures to deliver transaction-level accuracy, scalable BI, and GAAP-compliant revenue recognition—projects that have prevented multi-million dollar revenue errors and tripled system throughput. Comfortable owning end-to-end platforms, he partners across engineering, accounting, and compliance to turn complex financial rules into automated, auditable systems. A hands-on technologist with an MSc in Computer Science, he also contributes to open-source ML tooling (notably enhancements to the tensorflow-onnx converter), reflecting a curiosity that spans fintech systems and model-conversion engineering.
8 years of coding experience
16 years of employment as a software developer
Master of Science (M.Sc.), Computer Science, Master of Science (M.Sc.), Computer Science at Loughborough UniversityBachelor of Science - BS, Network and multimedia computing, Bachelor of Science - BS, Network and multimedia computing at Coventry University
English, Chinese
Github Skills (12)
keras10
tflite10
tensorflow10
onnx10
python10
convert9
converting9
exporter9
machine-learning9
deep-learning9
exports9
cicd8
Programming languages (6)
Github contributions (5)
onnx/tensorflow-onnx
Feb 2022 - Nov 2022
Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
Role in this project:
ML Engineer
ML EngineerContributions:7 releases, 157 reviews, 43 commits in 8 months
Contributions summary:Jay primarily contributed to the TensorFlow-ONNX project by enhancing its capabilities. They focused on integrating new TensorFlow 2.8.0 features, including support for TFLite ops and enabling it within the CI pipeline. Moreover, they addressed pylint issues and updated the default ONNX opset version to maintain compatibility and improve user experience. The user also added mappings for specific TFLite ops, demonstrating a strong understanding of model conversion.
tensorflowjsexportdeep-learningonnxkeras-tensorflow
fatcat-z/tensorflow-onnx
Nov 2021 - Oct 2022
Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
Contributions:6 PRs, 259 pushes, 100 branches in 11 months
onnxkeras-tensorflowtflite-modelstensorflowtensorflow-js
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.