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Senior Staff SWE / TLM @ Google DeepMind
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Interest/Skills: Natural Language Processing, Machine Learning, Deep Learning, Algorithms
University of Massachusetts Amherst
Master's degree, Computer Science
January 1, 2013 – January 1, 2015
Software Engineer Machine Learning
October 1, 2022 – Present
Amazon
Machine Learning Scientist
April 1, 2016 – October 1, 2022
BBN Technologies
Staff Scientist
September 1, 2015 – April 1, 2016
Amazon
SDE Intern
July 1, 2014 – September 1, 2014
Seattle
Alumni Association UMass, Amherst
Graduate Research Assistant
September 1, 2013 – August 1, 2015
Atos
Atos IT Challenge
December 1, 2011 – May 1, 2012
Parameterized Concept Weighting
October 1, 2014 – December 1, 2014
Implemented Parameterized Concept Weighting using Lucene to improve precision, recall on long queries
Semi-supervised Entity Extraction
February 1, 2014 – May 1, 2014
Entity Extraction from scientific text using semi-supervised approaches
Personal Virtual Assistant
February 1, 2013 – April 1, 2013
Performed basic tasks such as make calls, messaging, reminders, find appropriate places based on user query. Used trigram model for classification of input. Sentence Structure analysis was used to correct classification errors & process input. System learnt user specific information & also referenced pronouns to the person of interest.
Freescale Smart Car
July 1, 2011 – October 1, 2011
Designed an algorithm based on the PID (Proportional–Integral–Derivative) principle for a four wheel car fixed with a 128x1 pixel camera to achieve automatic navigation. Software development involved detecting the motion & direction of the car and ensure self-correction to stay on course on a track. Algorithm implementation was robust to handle a variety of lighting conditions.
Cultural Fit Analysis
The candidate has a strong background in research and development within large tech companies (Google, Amazon, BBN Technologies), indicating a fit for fast-paced, innovation-driven environments. The personal projects demonstrate initiative and a diverse interest in areas like AI, search, and embedded systems. However, the primary focus on Machine Learning and AI, with limited recent Android-specific experience, presents a potential misalignment with a dedicated 'Android Developer' role, suggesting a need to assess their interest and recent engagement with the Android ecosystem.
Soft Skills & Operational Fit
The candidate's experience as a Tech Lead Manager and Machine Learning Scientist at top-tier companies suggests strong problem-solving, leadership, and collaboration skills. The project descriptions, while brief, indicate an ability to tackle complex technical challenges. However, without specific psychometric test results, a detailed assessment of work attitude, stress handling, and team collaboration is not possible.