Summary
Jarred Barber is a Staff Research Engineer with 11 years of experience applying machine learning, probabilistic modeling, and signal/image processing to real-world problems across defense, satellite imagery, consumer speech, and large-scale generative AI. Currently at Google DeepMind, he tech-leads Muse text-to-image work and pilots new algorithms for efficient reasoning in language models, building on prior roles leading ML efforts at Amazon Alexa and DARPA-funded programs. His background includes pioneering deep learning and statistical methods for synthetic aperture radar and electro-optical satellite imagery at MIT Lincoln Laboratory and FeatureX/Orbital Insight, blending physics-based models with modern neural approaches. Jarred’s work uniquely spans both theoretical Bayesian/statistical modeling and production-focused ML systems, enabling him to move ideas from research prototypes into deployed capabilities. Based in Somerville, MA, he pairs advanced degrees from Johns Hopkins and MIT with a track record of cross-disciplinary collaboration and tech leadership. An understated thread through his career is a persistent focus on tough signal-rich modalities (radar, satellite, multi-device audio) where domain knowledge materially amplifies ML performance.
11 years of coding experience
14 years of employment as a software developer
Advanced Study Program, Advanced Study Program at Massachusetts Institute of Technology
Johns Hopkins University
Bachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at Penn State University