Senior Machine Learning Scientist II at Adobe
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Machine learning scientist with a focus on deep learning, data science and computer vision. Working at Adobe is amazing. Awesome colleagues, great work place, learning something new every day and having fun while doing it.
ETH Zürich
Doctor of Philosophy - PhD, Machine Learning
January 1, 2006 – January 1, 2011
University of Hamburg
Diploma, Computer Science
January 1, 2000 – January 1, 2006
University of Hamburg
Bachelor's degree, Sign Language Interpretation and Translation
January 1, 1998 – January 1, 2000
Adobe
Senior Machine Learning Scientist II
September 1, 2017 – Present
Newton, MA
Harvard University
Lecturer and Research Scientist for machine learning, data science, statistical Bayesian inference
July 1, 2014 – June 1, 2017
Harvard University
Postdoctoral Fellow in machine learning and computer vision
May 1, 2011 – June 1, 2014
ETH Zurich
PhD Student / Research Assistant in machine learning, and computer vision
August 1, 2006 – March 1, 2011
Zürich Area, Switzerland
Beiersdorf
Student Assistant
October 1, 2004 – March 1, 2006
Hamburg Area, Germany
University of Hamburg
Student Research Assistant
November 1, 2003 – July 1, 2004
Hamburg Area, Germany
HITeC
Student Assistant
August 1, 2002 – October 1, 2003
Hamburg Area, Germany
University of Hamburg
Student Research Assistant
February 1, 2000 – June 1, 2001
Hamburg Area, Germany
Cultural Fit Analysis
The candidate's diverse experience across academia (Harvard, ETH Zürich) and industry (Adobe, Beiersdorf) suggests adaptability and a broad perspective. Their involvement in teaching and training, along with leading diverse teams, indicates a collaborative and knowledge-sharing mindset. The focus on cutting-edge research and practical application aligns with a culture of innovation and continuous learning. The breadth of skills and project types (document intelligence, medical imaging, scene recognition) demonstrates versatility.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, teamwork, and teaching skills through their roles at Adobe and Harvard. Their experience in leading innovation projects and training engineers suggests excellent operational fit for driving ML initiatives and fostering technical growth within a team. The long tenure at Adobe and Harvard indicates stability and commitment.