AI 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
Engineering Leader, Machine Learning at Meta | 10+ years building billion-scale recommender systems
Amey Dharwadker has over a decade of experience in Artificial Intelligence and Machine Learning, both from an academic and industrial standpoint. He currently works as an AI Engineering Manager at Meta, leading the Facebook Video Recommendations Ranking team building personalization models used by over two billion users everyday! He has been instrumental in driving a significant increase in user engagement and revenue for the company through his work on News Feed, Ads and Videos ranking organizations. Prior to that, he also worked on computer vision based Advanced Driver Assistance System (ADAS) algorithms at Analog Devices. As an active researcher, he has published several international publications and patents in the fields of recommender systems and machine learning. In addition, he serves as a program committee member and reviewer for top AI/ML conferences including ICLR, KDD, AAAI, WebConf, CIKM, AISTATS, IJCAI, RecSys, ECIR, ECAI, UMAP and peer-reviewed journals specializing in recommendation systems, information retrieval and deep learning. He is often invited to speak at events and provide expert insights and advice on AI and ML in prominent technology publications. As a thought leader, he is also committed to mentoring and advising students, ML engineers, data scientists and early-stage companies through his involvement in hackathons, angel syndicates and startup accelerators. He also serves on the juries of renowned global technology competitions, including the CES Innovation Awards, Edison Awards and Globee Information Technology Awards. [Everything I write here is purely based on personal experiences and opinions, and do not represent the views of any past or present employers]
Columbia University
Master of Science (M.S.), Electrical Engineering
N/A – Present
National Institute of Technology, Tiruchirappalli
Bachelor of Technology, Electronics and Communication Engineering
N/A – Present
Meta
Engineering Leader, Machine Learning
August 1, 2019 – Present
Meta
Senior Software Engineer, Machine Learning
January 1, 2018 – July 1, 2019
Meta
Software Engineer, Machine Learning
January 1, 2015 – December 1, 2017
Software Engineer Intern
June 1, 2014 – August 1, 2014
San Francisco Bay Area
Columbia University in the City of New York
Graduate Teaching Assistant
September 1, 2013 – December 1, 2014
New York City Metropolitan Area
Analog Devices
Automotive Vision Software Engineer
July 1, 2011 – June 1, 2013
Bengaluru, Karnataka, India
Indian Institute of Science
University Grants Commission (UGC) Research Intern
May 1, 2010 – July 1, 2010
Indian Statistical Institute, Kolkata
Undergraduate Research Intern
May 1, 2009 – July 1, 2009
Greater Kolkata Area
IEEE Senior Member
IEEE
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's long tenure and progression at Meta, a leading tech company, suggest a strong cultural fit for fast-paced, innovative environments. Their involvement in diverse projects, from recommendation systems to integrity and bias reduction, demonstrates adaptability and a broad interest in impactful ML applications. The academic background and early research internships also indicate a continuous learning mindset.
Soft Skills & Operational Fit
The candidate's experience at Meta, particularly in leadership roles, suggests strong problem-solving, strategic thinking, and cross-functional collaboration skills. Their ability to lead teams and drive significant product improvements indicates excellent operational fit for a senior ML Engineer role. The descriptions imply a results-oriented and impactful approach to engineering challenges.