Professor of Computer Science at Stanford University (Artificial Intelligence and Machine Learning)
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Assessing your cultural and operational fit
Stanford University
Doctor of Philosophy (PhD), Computer Science
January 1, 1998 – January 1, 2003
USP - Universidade de São Paulo
Engineer's degree, Mechatronics, Robotics, and Automation Engineering
January 1, 1993 – January 1, 1998
Virtue AI
Co-Founder & Chief Scientist
June 1, 2024 – Present
Visual Layer
Co-Founder, Chief Scientist & Board Observer
September 1, 2022 – April 1, 2026
XetData
Board Observer
October 1, 2021 – July 1, 2024
Stanford University
Professor of Computer Science
August 1, 2021 – Present
OctoML
Member Board of Directors
July 1, 2019 – September 1, 2024
Apple
Senior Director of AI and Machine Learning
August 1, 2016 – August 1, 2021
Greater Seattle Area
Dato, Inc.
Founder & CEO
March 1, 2013 – July 1, 2016
Greater Seattle Area
University of Washington
Amazon Professor of Machine Learning
August 1, 2012 – March 1, 2021
Flashgroup
Co-Founder
August 1, 2009 – October 1, 2012
Carnegie Mellon University
Finmeccanica Associate Professor
August 1, 2004 – July 1, 2012
Intel Corporation
Senior Researcher
September 1, 2003 – August 1, 2004
Cultural Fit Analysis
The candidate's background is heavily skewed towards academic research, AI/ML leadership, and entrepreneurship. While these roles demonstrate innovation and high-level technical acumen, the direct alignment with a Big Data Engineer role, which often involves specific data pipeline, infrastructure, and distributed systems work, is not explicitly evident. The diversity of roles across academia and industry, including board positions, suggests adaptability and broad technical interest, but the focus is not directly on core Big Data engineering practices.
Soft Skills & Operational Fit
The candidate's extensive leadership and co-founder roles suggest strong entrepreneurial drive, strategic thinking, and the ability to build and lead technical teams. Their academic positions indicate strong communication and mentorship skills. However, specific operational fit for a hands-on Big Data Engineer role is not explicitly detailed in the provided experience descriptions.