Summary
Brian Gawalt is a senior software engineer with 13 years of experience specializing in applied machine learning, statistics, and production-quality systems at Google in Mountain View. He builds LLM-backed assistance for managing Google Cloud infrastructure and has applied ML and metrics across storage analytics, network quality for Google Fi, and web indexing. His background includes predictive modeling at Upwork, text mining and Spark work at Quantifind, and a Ph.D.-level focus on sparse supervised and unsupervised text summarization from UC Berkeley. He pairs rigorous statistical thinking—using experiments to prove improvements—with pragmatic engineering that ships scalable, performant services. Notably, he blends research-grade methods (Bayesian models, ensemble classifiers) with hands-on software across Python, Scala, and large-scale analytics. Based in the Bay Area, he brings both deep academic training and extensive production experience optimizing complex data systems.
13 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.), EECS, Doctor of Philosophy (Ph.D.), EECS at University of California, Berkeley
B.S., Electrical Engineering, B.S., Electrical Engineering at University of Virginia