Jason Wang
Machine Learning Engineer at APACHE SOFTWARE FOUNDATION
Beijing, China
Summary
🤩
Rockstar🎓
Top SchoolJason Wang is a Machine Learning Engineer with 10 years of experience blending low-level systems engineering (C/C++, CUDA, Linux) and high-level ML development in Python across autonomous driving, perception fusion, and model deployment. He has shipped production features for AR HUD visualization, multi-sensor fusion, and vehicle integration at OEM scale, and has hands-on experience with BEV perception, trajectory prediction, and IMU/HDMap solutions. An active open-source contributor, Jason has strengthened PaddlePaddle tooling, FastDeploy model support, and TVM frontend integration—work that helped bridge model conversion and fast on-device inference. His background in IC design and EDA tooling gives him uncommon depth in performance-sensitive engineering and memory management, reflected in contributions to shared-memory utilities and model compression. Based in Beijing, he combines algorithm research, team leadership, and cross-team technical integration to drive end-to-end ML systems from prototype to deployment.
10 years of coding experience
6 years of employment as a software developer
Bachelor's degree, Integrated Circuit Design, Bachelor's degree, Integrated Circuit Design at 哈尔滨理工大学
Github Skills (24)
continuous-deployment10
c-language10
python10
machine-learning10
onnx10
ml-deployment10
tensorflow10
trainings10
paddlepaddle10
computer-vision10
cprogramming-language10
protobuffer10
modeling10
protobuf10
convert9
Programming languages (6)
Github contributions (5)
PaddlePaddle/PaddleX
Apr 2020 - Dec 2022
All-in-One Development Tool based on PaddlePaddle
Role in this project:
ML Engineer
ML EngineerContributions:4 releases, 63 reviews, 459 commits in 2 years 7 months
Contributions summary:Jason's commits primarily involve the modification of a shared memory management utility, particularly focusing on memory allocation and data copying within the `paddlex/cv/datasets/shared_queue/sharedmemory.py` file. They also modified documentation related to the image processing and model training procedures, while also fixing some install issues, and fixing and updating model and deployment. These changes suggest a focus on core framework infrastructure and model training processes, likely for machine learning tasks. They also did work for model compression.
paddlepaddleclassificationsegmentationdeploymentocr
PaddlePaddle/Paddle2ONNX
Sep 2020 - Jan 2023
ONNX Model Exporter for PaddlePaddle
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:8 releases, 598 reviews, 214 commits in 2 years 3 months
Contributions summary:Jason's commits primarily involve modifications to PaddlePaddle's ONNX model exporter, specifically focusing on operators within the `paddle2onnx/op_mapper` directory. They added support for new operators like `pixel_shuffle`, and `silu`, addressed shape inference and added optimized conversion methods for elementwise operators. The user also fixed bugs, and implemented enhanced functionality for the `MulticlassNMS` operator, indicating their work focuses on the integration of machine learning models within the ONNX framework.
onnxpaddlepaddleocrdeploydetection
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