Nestor Qin
Senior AI Software Engineer at NVIDIA
Redmond, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolNestor Qin is a Senior AI Software Engineer with nine years of experience building full-stack and AI-driven products, currently contributing to NVIDIA’s Coding AI Copilot. He blends deep learning and generative-AI expertise with practical web, mobile, and game development skills, having led teams at Troutwood and driven measurement and business-product work at Pinterest. Nestor is an active open-source contributor — notably adding Service Worker support and robustness improvements to the high-performance in-browser LLM engine web-llm — demonstrating a focus on making cutting-edge models work reliably in the browser. He holds a Master’s in Software Engineering from Carnegie Mellon and a BS in Computer Science from the University of Washington, and he enjoys turning research-grade AI into user-friendly products. Based in Redmond, he brings both hands-on implementation chops and technical leadership across architecture, tooling, and product delivery.
9 years of coding experience
5 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at University of WashingtonMaster's degree, Computer Software Engineering, Master's degree, Computer Software Engineering at Carnegie Mellon University
Chinese, English, Japanese
Github Skills (9)
service-worker10
typescript10
javascript10
typescripts10
web-development10
webgpu10
typescript-types10
llm9
webassembly7
Programming languages (6)
Github contributions (5)
mlc-ai/web-llm
Mar 2024 - Dec 2024
High-performance In-browser LLM Inference Engine
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:11 reviews, 40 PRs, 56 pushes in 8 months
Contributions summary:Nestor implemented Service Worker support, enabling in-browser LLM inference for web applications. They created examples demonstrating how to run the Web-LLM engine using the Service Worker API. The user also fixed an issue by comparing object values instead of references and added a heartbeat event to monitor Service Worker status. Furthermore, they refactored the service worker implementation to streamline the code.
llm-inferencedeep-learningllmtvmwebgpu
Neet-Nestor/WhatToEat
Nov 2017 - Dec 2018
Contributions:55 commits, 53 pushes, 1 branch in 1 year 1 month
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