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Machine Learning Manager at Google
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
I've been working on solving some incredible signal processing and machine learning challenges for over 10 years, focused on physiological data collected through wearable technology, starting with the Myo armband and continuing on to develop Focals smart glasses. Currently leading a team of machine learning and computer vision engineers at Google.
University of Toronto
MHSc, Clinical Engineering
January 1, 2010 – January 1, 2012
Carleton University
BEng (High Distinction), Biomedical and Electrical Engineering
January 1, 2006 – January 1, 2010
Software Engineer, Machine Learning Manager
June 1, 2020 – Present
Kitchener, Ontario, Canada
North
Machine Intelligence Lead
June 1, 2016 – June 1, 2020
North
Signal Processing Engineer
December 1, 2012 – June 1, 2016
Massachusetts General Hospital
Clinical Engineering Intern
May 1, 2012 – August 1, 2012
Boston, Sims Innovation lab
Healthcare Human Factors
Clinical Engineering Intern
September 1, 2011 – January 1, 2012
Toronto General Hospital
Holland Bloorview
Master's Thesis
September 1, 2010 – October 1, 2012
Systems and Computer Engineering, Carleton University
Bachelor's Thesis
September 1, 2009 – April 1, 2010
University of Toronto
Eye Tracking System - Undergraduate Student Researcher
May 1, 2009 – August 1, 2009
Cultural Fit Analysis
The candidate has a strong background in research and development, particularly in cutting-edge fields like machine learning and biomedical engineering. Their experience at Google and North (a company focused on innovative wearable technology) suggests an inclination towards fast-paced, technically challenging environments. However, the target role is 'Data Analyst', which is a significant shift from their primary experience in Machine Learning Engineering and Management. While their analytical skills are likely strong, the direct alignment with typical data analyst responsibilities (e.g., extensive SQL, dashboarding, business intelligence) is not explicitly demonstrated, which could impact cultural fit for a pure data analyst role.
Soft Skills & Operational Fit
The candidate's experience as a Machine Learning Manager and Machine Intelligence Lead suggests strong leadership, project management, and team collaboration skills. Their work on interdisciplinary teams (software, electrical, hardware) indicates adaptability and cross-functional communication abilities. The detailed descriptions of their roles at North and thesis work demonstrate a methodical approach to problem-solving and a focus on practical application.