Summary
Alan Davila is a Senior Software Engineer in Austin with 11 years of experience applying physics-trained problem solving to machine learning, large-scale data visualization, and high-throughput analytics. At KLA he built ML solutions and synthetic data generators for wafer-inspection DNNs, led QA automation that shrank regression cycles from 400 to 16 hours, and prototyped a GPU-backed analytics stack that achieved a 180x speedup for tens of billions of points. He combines hands-on Python/TensorFlow engineering, server-side Datashader visualization, and DevOps best practices to deliver sub-second interactive exploration of massive metrology datasets. A former high-energy physics researcher, he leverages parallel computing and ROOT/C++ experience to extract signals from noisy, data-dense environments—an unusual blend that helps bridge scientific rigor and production ML systems.
11 years of coding experience
11 years of employment as a software developer
BS (Summa Cum Laude), Physics, BS (Summa Cum Laude), Physics at The University of Texas at El Paso
PhD, High Energy Physics (Heavy Ion Collisions), PhD, High Energy Physics (Heavy Ion Collisions) at The University of Texas at Austin
Spanish, English