Nalin Chhibber
Software Development Engineer at Amazon
Old Toronto, Ontario, Canada
Summary
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Senior🎓
Top SchoolNalin Chhibber is a Software Development Engineer at Amazon with 13 years of experience bridging research and production-grade full‑stack engineering, specializing in Human-AI interaction and NLP. He earned an MMath in Computer Science from the University of Waterloo where he published HCI/AI/IR papers and worked as a graduate researcher and teaching assistant. Nalin has applied interactive machine learning and intelligent UI principles across industry roles at Autodesk, RSVP.ai, and as an intern at CERN, and contributes to open-source projects such as the Daemo crowdsourcing platform (front-end enhancements like auto-suggest and validation UX). A longtime GSoC mentor and former open-source contributor, he blends academic rigor with pragmatic product delivery and a knack for making complex ML systems more usable. Outside of work he’s an avid skier, swimmer, and runner—often testing interaction designs with real-world human factors in mind.
13 years of coding experience
6 years of employment as a software developer
Master's of Mathematics & Computer Science (M.Math CS), Master's of Mathematics & Computer Science (M.Math CS) at University of WaterlooKendriya Vidyalaya SangathanBachelor of Technology (B.Tech.), Bachelor of Technology (B.Tech.) at Guru Gobind Singh Indraprastha University
Stackoverflow
7,395reputation
726kreached
164answers
0questions
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Github Skills (17)
javascript10
html10
angular10
jquery9
requirejs9
css9
angularjs9
nodejs9
material-design9
angularjs-service6
http6
v86
amd6
angularjs-directive6
java6
Programming languages (4)
Github contributions (5)
crowdresearch/daemo
Jan 2016 - Mar 2016
The Daemo crowdsourcing platform
Role in this project:
Front-end Developer
Front-end DeveloperContributions:27 commits, 4 PRs, 15 comments in 1 month
Contributions summary:Nalin primarily contributed to the front-end aspects of the Daemo crowdsourcing platform. Their work included implementing frontend validations for registration, login, and forgot-password forms, ensuring a better user experience. They also added notification messages upon successful registration. Moreover, the user integrated auto-suggest functionality for dynamic values in the template authoring section, using jquery-textcomplete.
pythonethereummaterial-designpostgresangular
Nalinc/machine-learning
Oct 2015 - Nov 2015
Contributions:10 commits, 8 pushes, 1 branch in 1 month
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