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Engineering Manager, Machine Learning 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
University of Southern California
MS, Computer Science (AI / Intelligent Robotics)
January 1, 2005 – January 1, 2007
Sardar Patel University
B.E., Electronics & Communication
January 1, 2000 – January 1, 2004
Apple
Engineering Manager, Machine Learning
April 1, 2017 – January 1, 2023
Cupertino, CA
Apple
Machine Learning Engineer
October 1, 2014 – March 1, 2017
Cupertino, CA
Chegg Inc.
Sr. Applied Scientist
January 1, 2013 – September 1, 2014
Simply Hired
Sr. Applied Researcher
December 1, 2010 – January 1, 2013
University of Florida
Sr. Research Analyst
May 1, 2007 – December 1, 2010
DirecTV INC
Software Engineer Intern
May 1, 2006 – December 1, 2006
Indian Institute of Technology, Bombay
Research Assistant
September 1, 2004 – December 1, 2004
Cultural Fit Analysis
The candidate has a strong background in applied research and engineering roles within tech companies (Apple, Chegg, Simply Hired) and academic institutions. The transition from Machine Learning Engineer/Manager to a Data Analyst role might indicate a desire for a more focused analytical role, but the depth of ML experience could also suggest an overqualification or a different career trajectory. The diversity of projects (search, recommendations, healthcare analytics) indicates adaptability. However, without specific project details or cultural assessment data, a definitive cultural fit is hard to ascertain.
Soft Skills & Operational Fit
The candidate's experience as an Engineering Manager and Sr. Applied Scientist/Researcher suggests strong problem-solving, leadership, and independent work capabilities. The descriptions indicate a results-oriented approach, particularly in delivering gains in engagement and revenue metrics. However, specific soft skill assessments are not available.