Mey Khalili
Backend EngineerMachine learning engineer at Apple
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
Machine learning engineer 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
Specialties: deep learning, algorithm design, machine vision, image processing, robotics
Cornell University
Ph.D., Physical chemistry
January 1, 2002 – January 1, 2005
Cornell University
M.S., Electrical Engineering
January 1, 2000 – January 1, 2002
Apple
Machine learning engineer
December 1, 2018 – Present
San Francisco Bay Area
Lighthouse AI
Deep Learning Engineer
September 1, 2017 – December 1, 2018
San Francisco Bay Area
Apple
Software Engineer
October 1, 2015 – September 1, 2017
San Francisco Bay Area
Tesla Motors
Staff Engineer/Driver Assistance & Autopilot
August 1, 2014 – September 1, 2015
Palo Alto, California
Nokia
Principal Research Engineer
November 1, 2013 – July 1, 2014
Nokia
Senior Engineer
January 1, 2012 – November 1, 2013
MITRE
Senior Software Engineer
September 1, 2008 – December 1, 2011
Mclean, VA
University of Cambridge
Post-doctorate researcher
January 1, 2006 – January 1, 2008
Cornell University
Graduate student
January 1, 2000 – January 1, 2006
Cultural Fit Analysis
The candidate's background is heavily focused on Machine Learning, Deep Learning, and Computer Vision. While these are highly technical fields, the target role is 'Backend Engineer'. There is a potential mismatch in direct experience with traditional backend systems, distributed computing, or specific backend frameworks. The diversity of projects is not explicitly detailed, making it difficult to assess breadth beyond their specialized domain.
Soft Skills & Operational Fit
The provided data does not contain sufficient information to assess soft skills or operational fit beyond the roles held. The candidate has a long tenure in technical roles, suggesting dedication and problem-solving abilities.