Founder/CEO of deep learning startup
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Assessing your cultural and operational fit
I work in deep learning research, sometimes theory, but very much tilted toward the applied side. That means taking advantage of huge (often unlabeled) datasets and the latest GPU hardware. Taking approaches that work in the lab on academic datasets and scaling them up.
Columbia Engineering
MS, Computer Science
January 1, 2005 – January 1, 2005
Technion - Israel Institute of Technology
student summer program, Aerospace, Aeronautical and Astronautical Engineering
January 1, 2000 – January 1, 2000
University of Maryland
BS, Mathematics, Computer Science
January 1, 2000 – January 1, 2004
DeepNFTValue
Chief Executive Officer
June 1, 2022 – Present
Miami, Florida, United States
Point72
Research Team Lead
November 1, 2019 – January 1, 2022
New York City Metropolitan Area
NVIDIA
Applied Deep Learning Researcher
March 1, 2017 – November 1, 2019
San Francisco Bay Area
Software Engineer
January 1, 2016 – February 1, 2017
PokerPoker, LLC
Founder/developer
May 1, 2014 – October 1, 2015
Quantifind
Software Engineer
October 1, 2013 – April 1, 2014
Chadwick
Founding hacker
January 1, 2009 – January 1, 2012
Brooklyn, NY
Software Engineer
August 1, 2005 – October 1, 2008
Cultural Fit Analysis
The candidate's diverse experience across startups, large tech companies, and finance, coupled with founding roles, suggests a high degree of adaptability and a proactive approach. The shift from deep learning research to a Big Data Engineer role indicates a potential interest in foundational data infrastructure, which could be a good fit for a dynamic environment. However, the recent CEO role might indicate a preference for strategic leadership over hands-on engineering, which needs to be validated.
Soft Skills & Operational Fit
The candidate's career trajectory, including founding roles and leadership positions, suggests strong initiative, problem-solving abilities, and an entrepreneurial mindset. Experience at various companies, from startups to large corporations, indicates adaptability. However, specific details on collaboration and operational fit are not explicitly provided in the descriptions.