Help & Supportcareers@gravityer.com
Machine Learning Software Engineer 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
An enthusiastic machine learning software engineer with a focus in deep learning, computer vision, and natural language processing. I enjoy the application of state-of-the-art research to solving challenging real-world problems. Expertise: • Deep Learning • Computer Vision • Large Language Models • Natural Language Processing • Reinforcement Learning • Robotics
University of Toronto
Master of Engineering, Mechanical and Industrial Engineering
January 1, 2016 – January 1, 2017
The University of British Columbia
Bachelor of Applied Science (BASc) with Co-op Standing, Mechanical Engineering
January 1, 2010 – January 1, 2015
Webber Academy
High School Diploma
January 1, 2004 – January 1, 2010
Machine Learning Software Engineer
April 1, 2020 – Present
Mountain View, California, United States
Motorola Mobility (a Lenovo Company)
Staff Researcher, Deep Learning
August 1, 2017 – April 1, 2020
Chicago, IL
University of Toronto
Graduate Teaching Assistant - Fundamentals of Computer Programming
January 1, 2017 – July 1, 2017
Toronto, Ontario, Canada
University of Toronto
Graduate Research Assistant
May 1, 2016 – October 1, 2017
Toronto, Ontario, Canada
CF Industries
Mechanical Engineering Co-op Student
January 1, 2014 – August 1, 2014
Medicine Hat, Alberta
Absolute Completion Technologies
Mechanical Engineering Co-op Student
May 1, 2013 – August 1, 2013
Edmonton, Alberta
WorleyParsons
Project Controls Co-op Student
May 1, 2012 – December 1, 2012
Calgary, Alberta
Pedal-Powered Charging Station
September 1, 2014 – May 1, 2015
Worked in a team of five final-year engineers to design and construct a pedal-powered station for the Alma Mater Society of the university. The pedal-powered station was intended to be located in the new Student Union Building, called the Student Nest, which finished in May 2015. The device allows students to create their own electricity to charge their portable devices by pedaling, while also providing valuable education on mechanical and electrical principles and sustainability. Utilizes a car differential running in reverse to combine pedaling power from multiple users and encourage collaboration.
Udacity Deep Learning Nanodegree
Udacity
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong academic background and experience with large tech companies (Google, Motorola Mobility). Their project experience, while not directly related to data analysis, shows a collaborative and innovative spirit. However, the target role of 'Data Analyst' is a significant pivot from their core expertise in Machine Learning/Deep Learning. While the candidate possesses strong technical skills, the direct cultural fit for a dedicated data analyst role, which often involves specific tools and methodologies (e.g., SQL, BI tools, statistical analysis beyond ML model evaluation), is not clearly demonstrated by their past roles or projects. Their experience is heavily skewed towards ML engineering and research, which might not align with the day-to-day responsibilities and focus of a typical Data Analyst.
Soft Skills & Operational Fit
The candidate's experience as a Graduate Teaching Assistant and involvement in team projects (Pedal-Powered Charging Station) suggest good communication and collaboration skills. Their research roles indicate problem-solving and analytical abilities. However, the target role is 'Data Analyst', which is a significant shift from their primary experience in Machine Learning Software Engineering and Deep Learning Research. While analytical skills are transferable, the specific operational fit for a pure Data Analyst role without explicit data analysis project experience is not strongly evident.