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Senior Machine Learning Manager at Apple
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Technical University of Munich
Doctor of Science (Dr. rer. nat.), Computer Science
January 1, 2012 – January 1, 2014
大阪大学 - Osaka University
Special Research Student, Computer Science
January 1, 2007 – January 1, 2008
Bauhaus-Universität Weimar
Master of Science (M.Sc.), Media Systems (Computer Science for Media)
January 1, 2006 – January 1, 2010
Bauhaus-Universität Weimar
Bachelor of Science (B.Sc.), Media Systems (Computer Science for Media)
January 1, 2003 – January 1, 2006
Apple
Senior Engineering Manager (Machine Learning Algorithms for Vision Pro, Siri)
October 1, 2019 – Present
San Francisco Bay Area
Apple
Engineering Manager (Machine Learning Algorithms for ARKit, Vision Pro)
September 1, 2015 – October 1, 2019
San Francisco Bay Area
Metaio
Head of Advanced Technologies Group (Computer Vision, Augmented Reality)
January 1, 2014 – August 1, 2015
Metaio
Senior Software Developer (Computer Vision, Augmented Reality)
January 1, 2012 – December 1, 2013
Metaio
Software Developer (Computer Vision, Augmented Reality)
February 1, 2010 – December 1, 2011
Cultural Fit Analysis
The candidate's extensive experience at Apple and Metaio, including founding and leading an advanced technologies group, suggests a strong fit for innovative, fast-paced, and research-driven cultures. Their work on cutting-edge technologies like Vision Pro and ARKit aligns with companies pushing technological boundaries. The lack of explicit project diversity outside of AR/ML/CV might indicate a specialized focus, but within that domain, their breadth is significant.
Soft Skills & Operational Fit
The candidate's experience as an Engineering Manager and Head of Advanced Technologies Group demonstrates strong leadership, team management, and strategic planning skills. Their role in driving product features and managing large-scale data collections suggests excellent operational fit for complex technical environments. The descriptions imply strong problem-solving and innovation capabilities.