
Senior Software Engineer - Machine Learning at Google Research
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
I am a Masters Student in Computer Science at University of California, San Diego. I am interested in a full time position as a Machine Learning Engineer.
UC San Diego
Master’s Degree, Computer Science
January 1, 2014 – January 1, 2015
Imperial College London
Study Abroad, Computer Science
January 1, 2011 – January 1, 2012
UC San Diego
B.S, Computer Science
January 1, 2009 – January 1, 2014
Senior Software Engineer - Machine Learning
June 1, 2019 – Present
Uber Advanced Technologies Group
Machine Learning Engineer
January 1, 2018 – June 1, 2019
San Francisco, California
Rocket Fuel Inc.
Machine Learning Engineer
April 1, 2016 – December 1, 2017
Redwood City, California
University of California, San Diego
Teaching Assistant
June 1, 2014 – December 1, 2015
University of California, San Diego
Graduate Student Researcher
May 1, 2014 – June 1, 2015
UCSD
Student Research under Prof. Ramamohan Paturi
February 1, 2014 – May 1, 2014
University of California, San Diego
CSE Tutor
December 1, 2013 – June 1, 2014
A*STAR - Agency for Science, Technology and Research
Student Researcher
June 1, 2013 – August 1, 2013
University of California, San Diego
Exploratory Research with Prof. Nadir Weibel
January 1, 2013 – June 1, 2013
Cisco Systems, Inc
Engineering Intern
July 1, 2012 – September 1, 2012
USCMS/UCSD
Programmer
March 1, 2011 – June 1, 2011
National Geographic Engineers for Exploration
Programmer
December 1, 2010 – June 1, 2011
La Jolla, CA
Cultural Fit Analysis
The candidate's diverse experience across research institutions (Google Research, Uber ATG, UCSD) and industry (Rocket Fuel) suggests adaptability to various work environments. Their involvement in projects related to fairness and robustness of ML models aligns with ethical AI development, which is a positive cultural indicator. The breadth of their academic and professional projects, from theoretical computer science to practical ML applications, indicates a curious and versatile individual. The target role of ML Engineer aligns well with their career trajectory.
Soft Skills & Operational Fit
The candidate's resume indicates a strong research orientation and experience in collaborative academic and industry settings. Roles as a Teaching Assistant and Tutor suggest good communication and mentoring skills. The descriptions imply a problem-solving mindset and ability to work on complex, cutting-edge ML problems. However, without specific assessment data, a definitive evaluation of soft skills and operational fit is limited.