Director of Engineering at Salesforce specializing in ML Platforms
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Assessing your cultural and operational fit
University of Illinois Chicago
Master's degree, Computer Science
January 1, 1998 – January 1, 2000
University of Madras
Bachelor of Science (BS), Computer Science
January 1, 1994 – January 1, 1998
Salesforce
Director of Engineering, ML Platform
August 1, 2022 – Present
Salesforce
Senior Manager, ML Platform
September 1, 2020 – August 1, 2022
Salesforce
Principal Software Engineer
November 1, 2018 – September 1, 2020
Microsoft
Senior Software Engineer ( Azure Machine Learning)
January 1, 2014 – September 1, 2018
Microsoft
Senior Software Engineer (Cloud + Enterprise, SQL Information services)
May 1, 2012 – December 1, 2013
Microsoft
Software Engineer 2 (Server and Tools)
January 1, 2006 – April 1, 2012
Microsoft
Software Engineer
July 1, 2002 – December 1, 2005
Machine Learning
Stanford University
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a long tenure at large, established tech companies (Microsoft, Salesforce), indicating an ability to thrive in structured environments. Their career progression from individual contributor to director level suggests ambition and a growth mindset. The focus on ML platforms and big data aligns well with modern data-driven cultures. However, the lack of diverse project types outside of large corporate environments might indicate a preference for established processes over startup agility, which could be a factor depending on the target company's culture.
Soft Skills & Operational Fit
The candidate's progression into leadership roles (Director of Engineering, Senior Manager) at Salesforce suggests strong leadership, project management, and team collaboration skills. Experience in building ML platforms implies an ability to work cross-functionally and drive complex initiatives. However, without specific psychometric test results, a detailed assessment of work attitude, stress handling, and direct team collaboration is limited.