Machine Learning @ Twitter Cortex
San Francisco, California
Probabilistic Computation Project at MIT CSAIL
BayesDB Lead Developer (Research Engineer and M.Eng. Student)
January 2013 to August 2014
Diffeo
Software Engineering Intern (Machine Learning)
June 2013 to September 2013
Cambridge, MA
Software Engineering Intern
June 2011 to August 2011
Numenta
Software Development Intern
June 2010 to August 2010
Elastic Intelligence
Software Engineering in Test Intern
July 2009 to August 2009
Computer History Museum
Volunteer Archivist
June 2007 to August 2007
Senior Machine Learning Engineer
San Francisco Bay Area
MIT Media Lab
Undergraduate Researcher in the Human Dynamics Group
November 2009 to May 2010
Palantir Technologies
Software Engineer Intern
May 2012 to August 2012
Palo Alto, CA
Massachusetts Institute of Technology
Master of Engineering (MEng), Electrical Engineering and Computer Science, 5.0/5.0
2013 to 2014
Massachusetts Institute of Technology
Bachelor of Science (BS), Computer Science and Engineering, 4.8/5.0
2009 to 2013
Menlo School
High School
2005 to 2009
Lead developer of BayesDB (http://probcomp.csail.mit.edu/bayesdb/), a Bayesian database table that lets users query the probable implications of their tabular data as easily as an SQL database lets them query the data itself. Lead developer of BayesDB (http://probcomp.csail.mit.edu/bayesdb/), a Bayesian database table that lets users query the probable implications of their tabular data as easily as an SQL database lets them query the data itself.
What company does Jay Baxter work for?
Jay Baxter works for Probabilistic Computation Project at MIT CSAIL
What is Jay Baxter's role at Probabilistic Computation Project at MIT CSAIL?
Jay Baxter is BayesDB Lead Developer (Research Engineer and M.Eng. Student)
What industry does Jay Baxter work in?
Jay Baxter works in the Computer Software industry.
Who are Jay Baxter's colleagues?
Jay Baxter's colleagues are David Sourenian, Apoorva Bansal, Art Malinin, Chen-Rui Chou, Dan Bress, Lyee Chong, Gregory Fast, Daniel Anderson, Satoshi Nakagawa, and Kyle Rosenberg
💼 Past Experience
Work Experience:Machine Learning @ Twitter CortexBayesDB Lead Developer (Research Engineer and M.Eng. Student) at Probabilistic Computation Project at MIT CSAIL from January 2013 to August 2014 (1 year 8 months)Software Engineering Intern (Machine Learning) at Diffeo from June 2013 to September 2013 (4 months) in Cambridge, MASoftware Development Intern at Google from June 2011 to August 2011 (3 months)Software Development Intern at Numenta from June 2010 to August 2010 (3 months)Software Engineering at elastic intelligence from July 2009 to August 2009 (2 months)Volunteer Archivist at Computer History Museum from June 2007 to August 2007 (3 months)Senior Machine Learning Engineer at Twitter in San Francisco Bay AreaMachine Learning Engineer at Palantir Technologies from May 2012 to August 2012 (4 months) in Palo Alto, CA
🎓 Education
Jay Baxter's education and work readiness background can be outlined in three areas: engineering, computer science, and engineering. Baxter's MEng from MIT gave him a strong background in electrical engineering and computer science. This experience has helped him develop his work readiness in these areas. Overall, Baxter is highly competent in areas of engineering and computer science, which has helped him achieve numerous successions in his career.
💡 Technical & Interpersonal Skills
Jay Baxter is currently a BayesDB Lead Developer (Research Engineer and M.Eng. Student) at Probabilistic Computation Project at MIT CSAIL from January 2013 to August 2014 (1 year 8 months). Lead developer of BayesDB (http://probcomp.csail.mit.edu/bayesdb/), a Bayesian database table that lets users query the probable implications of their tabular data as easily as an SQL database lets them query the data itself.Software Engineering Intern (Machine Learning) at Diffeo from June 2013 to September 2013 (4 months) in Cambridge, MA. Worked on cross-document entity resolution (coreference) and entity-based search by developing hierarchical probabilistic models and their associated inference algorithms, including structure learning and semi-supervised parameter learning. Software Engineering Intern at Google from June 2011 to August 2011 (3 months). Launched and developed Google Book Alerts, a Google Alerts feature that emails users when new books that match users' queries become available. Software Development Intern at Numenta from June 2010 to August 2010 (3 months). Developed part of NuPIC 2, a tool to use a neocortex-based learning algorithm that automatically finds patterns in data streams in order to make predictions. Software Engineering in Test Intern at Elastic Intelligence from July 2009 to August 2009 (2 months). Performed automated testing on a product that generates human-friendly reports from web service output. Volunteer Archivist at Computer History Museum from June 2007 to August 2007 (3 months). Cataloged computer hardware donations. Senior Machine Learning Engineer at Twitter in San Francisco Bay Area.Senior Machine Learning Engineer at Twitter in San Francisco Bay Area.
Introversion (I), Sensing (S), Thinking (T), Perceiving (P)
0 year(s), 5 month(s)
Unlikely
Likely
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