S Brubaker
Staff Software Engineer at Udacity
Marietta, Georgia, United States
Summary
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Rockstar🎓
Top SchoolS. Brubaker is a Staff Software Engineer with 11 years of experience building scalable education technology at Udacity, where he’s led major re-architectures of browser-based development environments and overhauled the content management system to enable versioning and reusable modular content. He previously designed high-throughput automatic grading infrastructure and led the reviews system, implementing policy-based access control, payments integration, and plagiarism detection to protect learners and mentors. With a PhD in Computer Science and experience teaching at Georgia Tech, he combines rigorous academic foundations with pragmatic product engineering. His open-source work includes refactoring RNN teaching materials for autograder compatibility, reflecting a focus on reproducible ML education and assessment. Based in Marietta, Georgia, he pairs systems-level architecture skills with a knack for turning pedagogical requirements into robust, production-ready tooling.
11 years of coding experience
8 years of employment as a software developer
St. Anselm's Abbey SchoolDoctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at Georgia Institute of TechnologyBachelor of Science (BS), Engineering, Bachelor of Science (BS), Engineering at Swarthmore College
Stackoverflow
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Github Skills (8)
keras10
machine-learning10
time-series10
rnn-model10
python10
n10
data-analysis10
jupyter-notebook9
Programming languages (7)
Github contributions (5)
udacity/aind2-rnn
May 2017 - Jul 2017
Project materials for RNN segment of AIND nanodegree
Role in this project:
ML Engineer
ML EngineerContributions:12 commits, 2 PRs, 8 pushes in 1 month
Contributions summary:S refactored code for autograder compatibility, indicating a focus on project assessment and potentially the underlying structure for automated evaluation. They are working with an iPython notebook involving RNNs. Their contributions also involve implementing and refactoring code, potentially including time series transformation and model building. The presence of keras, suggests that the user has expertise in building and training neural networks.
pytorchrnnnanodegreedeep-learningmaterials-project
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