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Machine Learning & NLP
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Carnegie Mellon University
Master’s Degree, Natural Language Processing
January 1, 2015 – January 1, 2017
Ramaiah Institute Of Technology
Bachelor’s Degree, Computer Science
January 1, 2009 – January 1, 2013
MindMeld, Inc
Technical Lead
May 1, 2022 – Present
MindMeld, Inc
Senior Machine Learning Engineer
September 1, 2017 – May 1, 2022
Carnegie Mellon University
Graduate Research Assistant
August 1, 2016 – August 1, 2017
Pittsburgh
Carnegie Mellon University
Teaching Assistant
August 1, 2016 – December 1, 2016
Pittsburgh
Carnegie Mellon University
Graduate Research Assistant
August 1, 2015 – July 1, 2016
Pittsburgh
Infinera
System Software Developer
November 1, 2014 – June 1, 2015
Bangalore, India
Akamai Technologies
SQA Engineer
July 1, 2013 – October 1, 2014
Bangalore, India
Cultural Fit Analysis
The candidate has a strong academic background and experience in both industry and research. The transition from Machine Learning/NLP to a Backend Engineer role suggests adaptability, but the direct alignment with a pure backend role needs further validation. The diversity of roles (research, teaching, SQA, system software, ML engineering, technical lead) indicates a broad skill set and potential for cross-functional contributions. However, the primary focus on ML/NLP might require a shift in focus for a pure backend role.
Soft Skills & Operational Fit
The candidate's experience as a Technical Lead and Teaching Assistant suggests leadership, mentorship, and communication skills. Research assistant roles indicate problem-solving and analytical abilities. However, specific details on collaboration, stress handling, or work attitude are not available from the provided data.