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Machine Learning Engineer
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 Toronto
Master of Science in Applied Computing (M.Sc.Ac.)
January 1, 2016 – June 1, 2018
National Tsing Hua University
Bachelor, Electrical Engineering
January 1, 2010 – January 1, 2014
彭博資訊
Senior ML Ops Engineer
March 1, 2026 – Present
New York City Metropolitan Area · Hybrid
Career Break
Personal goal pursuit
February 1, 2025 – February 1, 2026
Greater Toronto Area, Canada
Meta
Senior Software Engineer, Machine Learning
October 1, 2022 – January 1, 2025
Toronto, Ontario, Canada · Remote
Nylas
Senior Machine Learning Engineer
August 1, 2020 – September 1, 2022
Toronto
Paytm Labs
Machine Learning Engineer
April 1, 2019 – July 1, 2020
Toronto
ROSS Intelligence
Machine Learning Engineer
May 1, 2017 – February 1, 2019
Toronto, Canada Area
University of Toronto
Teaching Assistant - Machine Learning and Data Mining
September 1, 2016 – December 1, 2016
Department of Computer Science
Academia Sinica
Reseach Assistant
August 1, 2015 – June 1, 2016
Taipei City, Taipei City, Taiwan
ITRI
Summer Intern
July 1, 2013 – August 1, 2013
Hsinchu City, Taiwan, Taiwan
Deep Learning and Reinforcement Learning Summer School
CIFAR
June 24, 2026 – Present
Convex Optimization
Stanford Online
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
Social and Economic Networks: Models and Analysis
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has worked in diverse environments, from large tech companies like Meta to startups like Nylas and ROSS Intelligence, indicating adaptability. The career break might suggest a focus on personal growth, which could align with a culture that values work-life balance and continuous learning. However, the project descriptions are primarily technical, making it difficult to assess cultural fit beyond a general alignment with a technically driven environment. The target role of ML Engineer aligns well with the candidate's experience.
Soft Skills & Operational Fit
The candidate's resume indicates a strong focus on technical roles and problem-solving within ML contexts. The career break for 'Personal goal pursuit' suggests a capacity for self-direction, but without further information, it's difficult to assess specific soft skills or operational fit beyond technical contributions. The descriptions of past roles imply an ability to work on complex, scalable systems.