
Tech Lead, Staff ML Engineer at Google
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Assessing your cultural and operational fit
Georgia Institute of Technology
Doctor of Philosophy (PhD), Mathematics
January 1, 2010 – January 1, 2014
Yerevan State University
BS and MS, Mathematics
January 1, 1999 – January 1, 2005
ML Engineer / Tech Lead
August 1, 2019 – Present
Greater Seattle Area · On-site
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Software Development Engineer
June 1, 2014 – February 1, 2017
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October 1, 2007 – May 1, 2010
CQG
Software Developer
November 1, 2005 – June 1, 2007
Unicad
Software Engineer
June 1, 2004 – April 1, 2005
Yerevan, Armenia
Cultural Fit Analysis
The candidate's career trajectory, moving from general software development to specialized ML engineering roles at prominent companies like Amazon and Google, demonstrates adaptability and a drive for continuous learning. The diversity of ML projects (LLMs, CV, NLP, RL, Recommender Systems, time series analysis) indicates a broad interest and ability to contribute to various initiatives, aligning well with dynamic, innovation-driven cultures. The long tenure at Google as an ML Engineer/Tech Lead suggests stability and commitment.
Soft Skills & Operational Fit
The candidate's extensive experience at leading tech companies suggests strong operational fit and ability to work in high-performance environments. The PhD in Mathematics implies strong analytical rigor and problem-solving capabilities. While direct soft skill assessment data is not provided, the progression into a Tech Lead role at Google indicates leadership and collaboration potential.