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Senior Director of AI/ML at Upwork
AI executive and researcher with a strong interest in reliable, production-ready AI. I lead teams of 50+ people on complex AI R&D efforts, and am especially concerned with developing AI algorithms that bring promising AI ideas into robust production quality. I have grown AI research organizations at both mature (e.g. GM Cruise) and nascent (e.g. Upwork Inc) companies, with proven success at taking an AI organization from zero to production and research readiness. My work at Cruise and Upwork resulted in both large-scale improvements to their respective AI products, as well as the inaugural top-tier AI publications for both companies. I not only work in a critically overlooked area (reliability/robustness) for any company interested in productionizing AI, but have a track record as a force-multiplier for AI teams of all sizes and maturity levels. Publications: https://scholar.google.com/citations?user=ji6BSBoAAAAJ&hl=en
Harvard University
Bachelor of Arts (B.A.), Physics and Mathematics
N/A – Present
Stanford University
Master of Science (M.S.), Physics
N/A – Present
Stanford University
Doctor of Philosophy (PhD), Physics
N/A – Present
Stanford University
Doctor of Philosophy Minor (PMn), Statistics
N/A – Present
Upwork
Senior Director of AI/ML
January 1, 2025 – Present
San Francisco Bay Area
Stealth Startup
Founder and CEO
January 1, 2024 – January 1, 2024
Upwork
Director of AI/ML
January 1, 2024 – January 1, 2025
San Francisco Bay Area
Cruise
Staff Research Scientist
January 1, 2022 – January 1, 2024
San Francisco Bay Area
Waymo
Senior Research Scientist
January 1, 2020 – January 1, 2022
Waymo
Research Scientist
January 1, 2019 – January 1, 2020
Magic Leap
Lead Software Engineer, Deep Learning
January 1, 2019 – January 1, 2019
Magic Leap
Senior Software Engineer, Deep Learning
January 1, 2017 – January 1, 2019
Beehive AI
Machine Learning Consultant
January 1, 2017 – January 1, 2017
Burlingame, CA
Stanford University
Teaching Assistant, Convolutional Neural Networks for Visual Recognition (cs231n@Stanford)
January 1, 2017 – January 1, 2017
NVIDIA
Machine Learning Software Intern
January 1, 2016 – January 1, 2016
Santa Clara, CA
Stanford University
Independent Research in Machine Learning, Deep Learning, and Big Data
January 1, 2014 – January 1, 2017
SLAC National Accelerator Laboratory
Researcher in Physics
January 1, 2012 – January 1, 2017
Harvard University
Researcher in Physics
January 1, 2010 – January 1, 2011
The University of Tokyo
Researcher in Physics
January 1, 2010 – January 1, 2010
Tokyo, Japan
William & Mary
Researcher in Mathematics
January 1, 2009 – January 1, 2009
Williamsburg, Virginia
Harvard University
Teaching Assistant in Mathematics
January 1, 2008 – January 1, 2011
Cultural Fit Analysis
The candidate's diverse experience across academia, large tech companies (Waymo, Cruise, NVIDIA), and startups (Stealth Startup, Magic Leap, Beehive AI) indicates adaptability and a broad perspective. Their involvement in cutting-edge research and leadership roles in AI/ML suggests a proactive, innovative, and growth-oriented mindset, which would be a strong cultural fit for organizations focused on advanced technology and research. The transition from physics research to leading AI initiatives showcases intellectual curiosity and a drive for impact.
Soft Skills & Operational Fit
The candidate's career progression from research scientist to senior director, including founding a startup, demonstrates strong leadership, strategic thinking, and entrepreneurial drive. Their experience leading large teams and advising on company-wide AI strategy indicates excellent communication, collaboration, and operational management skills. The academic background and research output suggest a highly analytical and problem-solving oriented individual.