Wei-hsiang Wang
Backend Engineer at GoFreight
New Taipei, Taiwan
Summary
🤩
Rockstar🎓
Top SchoolWei-hsiang Wang is a backend engineer with 9 years’ experience building scalable, production-ready services using Python and Node.js, currently focused at GoFreight in New Taipei. He has strong DevOps chops—migrating serverless components to FastAPI/Gunicorn on AWS ECS with Terraform and improving WebSocket-driven human-in-the-loop flows—to boost automation and reliability in real-time detection systems. At Umbo he helped scale channels 10x while raising detection automation from 40% to 90%, and maintains data pipelines and MongoDB clusters for monitoring accuracy and latency. An active technical writer on the popular Python docs zh-tw repo, he contributes practical documentation fixes, and off-hours describes himself succinctly as “mostly python and cats,” hinting at a pragmatic, curious engineering style.
9 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BS, Mechanical Engineering, Bachelor of Science - BS, Mechanical Engineering at National Taiwan University
Japanese, Chinese, English
Stackoverflow
318reputation
6kreached
11answers
0questions
Github Skills (9)
read-me10
translation10
python10
documentation10
csv6
javascript6
mongodb6
excel6
numpy6
Programming languages (12)
Github contributions (5)
python/python-docs-zh-tw
Sep 2021 - Jan 2023
Traditional Chinese (zh-tw) translation of the Python Documentation
Role in this project:
Technical Writer
Technical WriterContributions:1326 reviews, 160 commits, 664 PRs in 1 year 4 months
Contributions summary:Wei-hsiang primarily contributed to the Python documentation repository by updating and correcting information within the README file. Their commits focused on fixing broken links, correcting invitation links, and updating version numbers. These changes involved modifying the README to reflect the current state of the documentation and correct inconsistencies. Additionally, the user added specific terms that don't have to be translated.
pythontranslation
mattwang44/LeNet-from-Scratch
Apr 2018 - Oct 2022
Implementation of LeNet5 without any auto-differentiate tools or deep learning frameworks. Accuracy of 98.6% is achieved on MNIST dataset.
Contributions:35 commits, 27 pushes, 1 branch in 4 years 6 months
deep-learningmnist-datasetlenetpython3mnist
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