Help & Supportcareers@gravityer.com
AI Researcher
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Researcher/engineer with a solid background in mathematical modeling, statistical analysis, and algorithms.
University of Calgary
Master’s Degree, Computer Science
January 1, 2016 – June 1, 2018
The University of British Columbia
Doctor of Philosophy - PhD, Mechanical Engineering
January 1, 2010 – January 1, 2014
The University of British Columbia
Master's degree, Mechanical Engineering
January 1, 2008 – January 1, 2010
Iran University of Science and Technology
Bachelor of Applied Science - BASc, Mechanical Engineering
January 1, 2003 – January 1, 2008
Normal Computing
Researcher
February 1, 2026 – Present
New York, United States · Hybrid
Mirage
Member of Technical Staff (Machine Learning)
May 1, 2025 – February 1, 2026
New York, New York, United States
Facebook AI
Research Engineer
August 1, 2020 – May 1, 2025
New York, United States
Machine Learning Engineer
September 1, 2018 – July 1, 2020
San Francisco Bay Area
Vevo
Machine Learning Engineer
February 1, 2018 – August 1, 2018
San Francisco Bay Area
Institute for Quantum Science and Technology
Research Assistant
May 1, 2016 – May 1, 2018
Calgary, Canada Area
Menrva Research Group
Postdoctoral Researcher
May 1, 2014 – December 1, 2015
Vancouver, Canada Area
Simon Fraser University
Postdoctoral Fellow
May 1, 2014 – December 1, 2015
Vancouver, Canada Area
LinaraLabs
Independent Software Developer
February 1, 2014 – December 1, 2015
Vancouver, Canada Area
ROV Consulting Inc.
Finite element stress analysis
March 1, 2013 – July 1, 2013
Kelowna, BC, Canada
Composites Research Network
Research Assistant
June 1, 2012 – April 1, 2014
The University of British Columbia
Research Assistant
September 1, 2008 – April 1, 2014
Cultural Fit Analysis
The candidate's career trajectory shows a strong focus on advanced research and machine learning, moving from academic research to industry roles at leading technology companies. This indicates a drive for innovation and technical excellence. The diverse educational background (Mechanical Engineering to Computer Science) and varied research topics (quantum algorithms, computational physics, NLP) suggest intellectual curiosity and adaptability. However, the lack of detailed project descriptions makes it challenging to assess collaboration styles or specific contributions to team environments, which are key aspects of cultural fit.
Soft Skills & Operational Fit
The candidate's extensive research background and roles at prominent tech companies suggest strong problem-solving, analytical thinking, and adaptability. The descriptions of past roles, though brief, indicate experience in complex technical domains. However, without specific project details or behavioral assessment data, it is difficult to fully assess soft skills like teamwork, leadership, or communication style.