Matthew Byrd

SDE II at Amazon

Hickory, North Carolina, United States
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Summary

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Senior
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Top School
Matthew Byrd is an SDE II with nine years of engineering experience who blends applied NLP research and full-stack web development to deliver production-ready systems. He holds an MS in Computer Science from UNC-Chapel Hill and was first author on an ACL 2022 paper predicting question difficulty, pairing interpretable NLP features with deep models and presenting results publicly. Matthew has built Django/React backends, Docker/AWS CI workflows, and research web apps that integrate computer vision for biology labs, including a Heroku-deployed video analysis tool and a published biology community contribution. At Epic he led efforts to de-identify data using transformers and regex, and he now continues his engineering career at Amazon, demonstrating a pattern of moving research prototypes into robust, client-facing software. Notably, he has bridged academia and industry by contracting with clients while simultaneously driving research projects that achieve both empirical results and deployed impact.
code9 years of coding experience
job5 years of employment as a software developer
bookMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at University of North Carolina at Chapel Hill
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Github Skills (60)

canvas-lms10
classifier10
autoencoder10
anomaly-detection9
lms9
classification9
anomaly-detection-algorithm9
django9
clustering9
mlmodel8
regression8
sklearn8
machine-learning8
javascript8
toolbox7

Programming languages (10)

TypeScriptJavaC++ShellSCSSJavaScriptHTMLRuby

Github contributions (5)

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ByrdOfAFeather/argus-web

Dec 2020 - Jun 2026

Multi-camera 3D data acquisition for consumer-grade cameras on the web
Contributions:21 pushes, 1 branch in 5 years 6 months
ByrdOfAFeather/NARC

Nov 2017 - Sep 2019

Senior Product- A Canvas LMS anomaly detection algorithm
Contributions:3 releases, 111 commits, 10 PRs in 1 year 9 months
anomaly-detection-algorithmcanvas-lmsanomaly-detectionautoencoderautoencoder-classification
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