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Jason Chaves has a diverse work experience spanning multiple industries. Jason started their career as a Research Assistant at Stanford University, where they worked on the EXO-200 Experiment. Their responsibilities included machine learning-based physics analysis and designing upgrades to detector electronics.

In 2014, they worked as a Summer Intern at MIT Lincoln Laboratory, where they developed software for a radar data recording/retrieval system. Jason also created a flexible data-loading API for users in Matlab.

From 2014 to 2015, they returned to Stanford University as a Graduate Research Assistant, collaborating on the EXO-200 Experiment and gaining experience in detector shift at the WIPP mine facility.

In 2015, Jason joined Raytheon as a Senior System Engineer. Jason worked on both Airborne and Space Programs and was involved in machine learning research and development. Their achievements include developing a Tensorflow-based deep convolutional neural network training framework and receiving a proposal award for an automatic target detection program.

Currently, they are employed at Epirus, where they hold the position of Director of System Engineering. Prior to this role, they served as the Systems Engineering Lead and Principal Systems Engineer. Additional information about their current role is not provided.

Jason Chaves completed a Bachelor of Science degree in Physics at Stanford University from 2010 to 2014. Jason pursued further studies at Stanford University and obtained a Master of Science degree in Electrical Engineering from 2013 to 2015.