Summary
Jonas Powell is a machine learning engineer in Berkeley with 9 years of experience bringing research-grade models into production across industry and academia. Trained as an astronomer, he combines strong statistical foundations (MCMC, Bayesian methods, time-series change detection) with practical ML engineering—building robust ETL pipelines, scalable models, and custom agent-based research tools at Rivian and prior DoD-focused work. He excels at taming messy, real-world data and has a track record of end-to-end delivery from proposal and exploration to deployment and customer-facing results. Comfortable implementing deep learning from scratch and automating high-value repetitive tasks, Jonas pairs curiosity-driven experimentation with product-minded rigor. An easy-going but driven collaborator, he uniquely leverages his astronomy background (300GB ALMA experience and a thesis that found interacting protoplanetary disks) to solve complex data problems.
9 years of coding experience
4 years of employment as a software developer
Bachelor of Arts (B.A.), Physics, College of Integrated Sciences, Bachelor of Arts (B.A.), Physics, College of Integrated Sciences at Wesleyan University
Lake Champlain Waldorf High School
French, English