Principal Systems Engineer
Jason's technical background spans machine learning, computer vision, adaptive radar signal processing, modeling/simulation, and high-performance computing. Jason began his career at Raytheon, initially as the SAR Mode Design lead for the ASARS-2B upgrade program, where he delivered several capability improvements. Later, Jason was a founding member of the Deep Learning team within Raytheon Space and Airborne Systems, building up an internal framework for developing object detection and classification systems that's been applied across multiple programs. Jason holds a B.S. in Physics and a M.S. in Electrical Engineering from Stanford University.