Dylan W is a results-driven software engineer with 9 years of experience building scalable, cloud-native systems and production ML pipelines, currently at Meta after recent staff roles focused on applied AI. He has a demonstrated knack for high-impact refactors and cost optimization—rewriting an 800k-line codebase down to 95k and cutting cloud costs by over 75% while maintaining zero downtime. His background spans recommender systems, RAG, web automation agents, and data layer unification for commerce search and recommendations at Adobe and Walmart. Dylan combines strong academic credentials in CS and ML from Georgia Tech with dual undergraduate degrees from UT Austin, blending research rigor with pragmatic engineering. He often ships prototype-first solutions to accelerate adoption of new computing paradigms and has driven measurable accuracy and efficiency gains in AI-driven products. Based in San Francisco, he pairs system-level architecture skills with hands-on implementation across languages and cloud platforms.
9 years of coding experience
9 years of employment as a software developer
Bachelor of Business Administration (BBA) Management Information Systems, Bachelor of Business Administration (BBA) Management Information Systems at The University of Texas at Austin
Master's of Science Computer Science and Machine Learning, Master's of Science Computer Science and Machine Learning at Georgia Institute of Technology
Contributions:2 PRs, 21 pushes, 4 branches in 29 days
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