Angela Wang
Software Engineer at Datadog
Old Toronto, Ontario, United States
Summary
👤
Senior🎓
Top SchoolAngela Wang is a software engineer with a multidisciplinary Computer Engineering background from the University of Waterloo and roughly eight years of hands-on experience across software, data, firmware, and robotics. She has shipped production and intern work at companies ranging from Datadog (alerting platform) to McAfee, Ocado Intelligent Automation, and BIONIK, blending backend and SRE-principles with embedded/robotics validation. Angela pairs engineering delivery with program leadership—she led logistics projects at Hack the North and has consulted on marketplace platforms—bringing both execution and stakeholder management to technical initiatives. Her open-source documentation work on TensorFlow's neural-structured-learning tutorials highlights an attention to developer experience and making complex ML concepts accessible. Now based in Toronto, she seeks roles that leverage data and robotics skills to build impactful, reliable systems.
8 years of coding experience
4 years of employment as a software developer
High School Diploma, MaCS Diploma (Math and Computer Science), High School Diploma, MaCS Diploma (Math and Computer Science) at William Lyon Mackenzie Collegiate InstituteBachelor of Applied Science - BASc, Computer Engineering, Bachelor of Applied Science - BASc, Computer Engineering at University of Waterloo
English, Chinese, French
Github Skills (6)
documentation10
technical-writing10
adversarial-learning9
neural-network8
tensorflow6
keras5
Programming languages (4)
Github contributions (5)
tensorflow/neural-structured-learning
Sep 2020 - Oct 2020
Training neural models with structured signals.
Role in this project:
Technical Writer
Technical WriterContributions:16 commits, 1 PR, 2 comments in 24 days
Contributions summary:Angela primarily contributed to the documentation of the adversarial learning tutorial within the neural-structured-learning repository. Their work included refining the tutorial content, correcting typos, rephrasing explanations for clarity, and updating the overall structure. The user also updated hyperlinks and reorganized the content, aiming to improve the tutorial's readability and provide a more comprehensive guide for beginners.
adversarial-learningautoencodergraph-learningstructureddeep-learning
andrew-zhan139/Ctrl-Air-Space
Jan 2021 - Jan 2021
Contributions:31 commits, 2 PRs, 28 pushes in 3 days
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