Stephen Sisk

Staff Software Engineer at Weights & Biases

Missoula, Montana, United States
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Summary

🤩
Rockstar
🎓
Top School
Stephen Sisk is a Staff Software Engineer with nine years of focused software engineering experience and a career that spans startups, large tech, and solo entrepreneurship. He has driven product and technical ownership at Weights & Biases and Google, leading cross-functional teams to deliver GDPR compliance, redesigned login and notification systems for millions of users, and production-grade UIs for GCP Dataflow. Equally comfortable in frontend and backend stacks, he has shipped systems in TypeScript/React, C#/ASP.NET, Java, and C++, and has a strong track record in metrics, monitoring, and scalable distributed systems. As a solo founder he built novel tooling—a PEG.js-powered spreadsheet language and event-driven, functional spreadsheet prototype for complex scenario planning—demonstrating an appetite for ambitious engineering challenges outside standard product constraints. He pairs hands-on coding with pragmatic leadership, having served as tech lead and program manager across teams that required coordination with legal, design, and open-source communities. Based in Missoula, Montana, he blends enterprise-grade engineering discipline with entrepreneurial curiosity.
code9 years of coding experience
job18 years of employment as a software developer
bookBS, Computer Science, BS, Computer Science at The University of Texas at Austin
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Github Skills (72)

python10
hyperparameter-optimization10
mlops10
deep-learning10
apache-beam10
collaboration10
streaming10
beam10
big-data10
latency10
api10
sql10
ai10
data-processing10
golang10

Programming languages (8)

TypeScriptJavaSCSSJavaScriptGoSwiftHTMLPython

Github contributions (5)

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ssisk/beam

Nov 2016 - Jul 2017

Contributions:4 PRs, 86 pushes, 34 branches in 8 months
javaapache-beamapachebeam
ssisk/beam-site

Feb 2017 - Jul 2017

Contributions:23 pushes, 12 branches in 4 months
javaapache-beamapachebeam
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Stephen Sisk - Staff Software Engineer at Weights & Biases