Zachary Wimpee is an AI scientist with a decade of experience applying physics- and math-driven rigor to data engineering and applied ML, now focused on designing and deploying large language model pipelines at scale. His career progressed from clinical analytics and EHR-focused data engineering to applied scientist and machine learning roles, giving him a rare combination of production-grade data infrastructure skills and model evaluation expertise in healthcare settings. He has hands-on experience converting legacy scientific codebases, building validation tooling, and operationalizing real-time AI engines that support predictive and NLP workloads. Based in San Angelo, Texas, Zachary pairs an academic foundation in physics and mathematics with practical data science training and two substantial capstone projects, signaling both theoretical depth and pragmatic engineering instincts. Notable but less obvious is his trajectory from low-level research (CERN, supersymmetry work) to product-facing AI delivery, demonstrating adaptability across research and production environments.
10 years of coding experience
5 years of employment as a software developer
Data Science, Data Science at Springboard
Bachelor's degree Physics and Mathematics, Bachelor's degree Physics and Mathematics at Angelo State University
Contributions:75 commits, 2 PRs, 65 pushes in 1 month
pytorchx-rayraydeep-learningcomputer-vision
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