Amanmeet Garg
Data AnalystAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
CV/ML Scientist at Amazon Prime Video
Amanmeet Garg is a Research Scientist and a leader with 12 years of experience (startups, Nielsen Media, Amazon) shipping CV/ML products and deep research. Aman's breadth of experience include Deep Learning based CV (Amazon Prime Video, Nielsen Media), Classical computer vision (MDAcne, LUUM robotics) and modern Deep Learning techniques such as Large Language Models, and CV foundation models. He has built Agentic AI automation systems at global scale in Amazon Prime Video, deep tech computer vision deployed on iOS mobile device, and Media Foundation Model at Amazon. His work has lead to 22 papers, 7 patents, 1200+ citations and delivered impact touching 200 Million customers across 180 countries generating in Billion dollar scale business value. His current research interests are in building spatial intelligence with Foundational Models and Generative AI and working on world models and vision language action model.
Simon Fraser University
Doctor of Philosophy (Ph.D.), Medical image analysis
January 1, 2011 – January 1, 2017
Simon Fraser University
Master of Science (M.Sc.), Biomedical Physiology and Kinesiology
January 1, 2008 – January 1, 2010
Punjab Engineering College
Bachelor of Engineering (B.Eng), Electrical Engineering
January 1, 2004 – January 1, 2008
Ajit Karam Singh International Public School
10th, High School
January 1, 1992 – January 1, 2002
Prime Video & Amazon Studios
CV / ML scientist
August 1, 2022 – Present
CurioEd
Investor
January 1, 2022 – June 1, 2025
Gracenote
Senior Applied Scientist
March 1, 2020 – August 1, 2022
Emeryville, California, United States
PiñataFarms
Computer Vision Research Engineer
May 1, 2019 – November 1, 2019
Los Angeles, California, United States
Foxeye Robotics
Computer Vision Research Engineer
November 1, 2018 – April 1, 2019
Berkeley, California
MDacne
Computer Vision and Deep Learning Engineer
November 1, 2017 – October 1, 2018
San Francisco Bay Area
Plantiga
Machine Learning Engineer
December 1, 2016 – August 1, 2017
Vancouver, British Columbia, Canada
eTreatMD
Research Engineer - mHealth, Image processing, Consultant
February 1, 2016 – June 1, 2016
Vancouver, Canada Area
MetaOptima Technology Inc.
Research and Development Engineer
August 1, 2015 – December 1, 2015
Vancouver, Canada Area
NeuroKinetics Health Services (B.C.), Inc.
Research Engineer
July 1, 2013 – June 1, 2014
Vancouver, Canada Area
Simon Fraser University
Graduate Teaching Assistant
September 1, 2012 – April 1, 2017
Simon Fraser University
PhD Research Assistant
January 1, 2011 – June 1, 2017
Mitacs
Accelerate program intern
January 1, 2010 – August 1, 2010
Simon Fraser University Burnaby
NeuroKinetics Health Services (BC) Ltd.
Research Engineer
December 1, 2009 – November 1, 2010
Simon Fraser University
Graduate Research Assistant (GRA)
August 1, 2008 – December 1, 2010
Goldman Sachs
Summer Intern
June 1, 2007 – July 1, 2007
Indian Institute of Technology, Kharagpur
Research Intern
December 1, 2006 – January 1, 2007
Kharagpur Area, India
Central Scientific Instruments Organization
Summer Intern
June 1, 2006 – August 1, 2006
Causal coupling in cardio-postural interactions
January 1, 2015 – Present
This project aims to identify and quantify the causal coupling in the cardio-postural interactions during orthostatic challenge. The project is in alignment with the research theme of wearable devices for continuous non-invasive monitoring and preventative intervention.
Cardiovascular and Postural changes during orthostatic challenge.
September 1, 2008 – December 1, 2010
Worked on experiments involving physiology data collection (ECG, EMG, BP, Posturography), Non stationary signal analysis, Wavelet signal processing, Statistical signal processing.
Statistical Analysis of fMRI Data
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily skewed towards research and development in computer vision and machine learning, often in academic or startup environments. While the target role is 'Data Analyst', the candidate's experience is more aligned with 'Data Scientist' or 'Machine Learning Engineer'. The project diversity is strong within the ML/CV domain, but there's a potential mismatch with a pure Data Analyst role which typically focuses more on business intelligence, reporting, and SQL/dashboarding, rather than model development and signal processing. The breadth of skills is high within their specialized domain, but less so for general data analysis tools.
Soft Skills & Operational Fit
The candidate's extensive research and project experience suggest strong problem-solving, analytical thinking, and independent work capabilities. The descriptions of deploying models and working on large-scale pipelines indicate an ability to translate research into practical solutions. However, specific soft skills like teamwork, leadership, or communication in a corporate setting are not explicitly detailed beyond technical contributions.