Software Engineer - AI for Integrity Leadership at Meta
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Geneva
PhD, Computer Science
January 1, 2009 – January 1, 2013
EPFL
MS, Computer Science
January 1, 2007 – January 1, 2009
Indian Institute of Technology, Delhi
Bachelor of Technology, Computer Science & Engineering
January 1, 2002 – January 1, 2006
Meta
Software Engineer
September 1, 2025 – Present
London Area, United Kingdom · On-site
Amazon
Principal Applied Scientist
October 1, 2022 – August 1, 2025
On-site
Amazon
Senior Applied Scientist
December 1, 2018 – September 1, 2022
On-site
Amazon
Applied Scientist II
April 1, 2015 – November 1, 2018
On-site
Amazon
Applied Scientist I
August 1, 2013 – March 1, 2015
On-site
Université de Genève
PhD Student
September 1, 2009 – August 1, 2013
IDIAP Research Institute
Intern
February 1, 2009 – August 1, 2009
International Computer Science Institute, University of California - Berkeley
Intern
August 1, 2008 – January 1, 2009
Yahoo!
Software Engineer
June 1, 2006 – May 1, 2007
Cultural Fit Analysis
The candidate has a strong background in research and large tech companies, which suggests a fit for fast-paced, data-driven environments. The academic background and roles as an Applied Scientist indicate a focus on innovation and complex problem-solving. However, the resume lacks explicit details on contributions to open-source, community involvement, or diverse team projects, which limits the assessment of broader cultural fit beyond technical excellence. The target role is 'Big Data Engineer', but the experience is heavily skewed towards 'Applied Scientist' with ML/CV/NLP, which might require a pivot in focus.
Soft Skills & Operational Fit
The candidate's career progression at Amazon suggests strong problem-solving, adaptability, and leadership skills. The PhD research indicates a capacity for independent work and deep analytical thinking. However, without specific project descriptions or behavioral assessment data, it is difficult to fully assess collaboration, communication, and stress handling.