Software Engineer at Amazon Fulfillment Technologies & Robotics
Old Toronto, Ontario, Canada
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Summary
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Rockstar
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Top School
Moaaz Sidat is a software engineer with 11 years of experience building scalable products across robotics, conversational AI, and developer platforms, currently contributing to Amazon Fulfillment Technologies & Robotics. He has led engineering at ETHGlobal where he built core infrastructure—MySQL migrations, a GraphQL API, tooling and payments—that powered 100+ global hackathons and new on-/off-chain product primitives. At Dialogue he scaled conversational systems and ML infra to support millions during the pandemic, later leading teams that automated medical triage and launched iCBT. A hands-on full-stack contributor, he’s active in open source (notably improving Rasa’s NLG interpolation and maintaining a popular React Native QR scanner) and balances software craft with hardware and robotics hacking. He also founded consumer and design-focused ventures, blending product design roots from uWaterloo with engineering leadership and a knack for shipping pragmatic automation. An uncommon strength is pairing deep production engineering with developer-experience work that empowers communities and events at scale.
11 years of coding experience
11 years of employment as a software developer
ODF6, ODF6 at On Deck Founder Fellowship
Graduate of GCE A Levels Mathematics Physics Chemistry Further Mathematics, Graduate of GCE A Levels Mathematics Physics Chemistry Further Mathematics at The City School PAF Chapter A Level
Startup School Online
Bachelor of Computer Science Specialization in Digital Design, Bachelor of Computer Science Specialization in Digital Design at University of Waterloo
Contributions:2 releases, 5 reviews, 183 commits in 4 years 6 months
Contributions summary:Moaaz primarily contributed to the development of the React Native QR code scanner component. They added core functionality, including the ability to scan QR codes and handle the scanned data. They also introduced features such as customizable UI elements, the ability to support full-screen scanning, and options to activate and deactivate the camera. The user further refined the component by addressing styling issues and improving the overall user experience.
💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
Role in this project:
Back-end Developer & ML Engineer
Contributions:1 review, 6 commits, 2 PRs in 1 year 2 months
Contributions summary:Moaaz contributed to the Rasa framework by adding support for interpolating and filling custom templates with slot values, enhancing the natural language generation capabilities. They made changes to the core nlg module, interpolator, and the template implementation. The user also added new tests to cover different cases including slot values, and edge cases using pytest. These changes demonstrate an understanding of and contributions to both the core Rasa framework, as well as its testing methodology.
nlupythonbotspeech-recognitionbotkit
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