Arbaz Khan
Backend EngineerML Infrastructure
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
ML Infrastructure
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Software engineer with ML/NLP educational background and industry experience building and delivering intelligent features end-to-end. Always interested in opportunities broadening hands-on experience and getting exposure to working on challenging problems.
Indian Institute of Technology, Kanpur
Master of Technology - MTech, Computer Science
January 1, 2013 – January 1, 2014
Indian Institute of Technology, Kanpur
Bachelor's degree, Computer Science
January 1, 2009 – January 1, 2013
Meta
Software Engineer
October 1, 2024 – Present
Menlo Park, California, United States
DoorDash
Staff Software Engineer, ML Infrastructure
March 1, 2020 – October 1, 2024
Mountain View, California, United States
Roam Analytics (acquired by Parexel)
Machine Learning Platform Engineer
December 1, 2016 – March 1, 2020
San Francisco Bay Area
Everstring (acquired by Zoominfo)
Backend Engineer
November 1, 2015 – December 1, 2016
San Francisco Bay Area
Oracle
Applications Engineer
October 1, 2014 – November 1, 2015
San Francisco Bay Area
Judge - Globee Awards for Technology
Globee Awards
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has worked at a diverse range of companies from large tech giants (Meta, DoorDash, Oracle) to startups (Roam Analytics, Everstring), indicating adaptability to different organizational cultures. Their focus on ML infrastructure aligns well with a Backend Engineer role, especially one involving machine learning systems. The breadth of experience across different problem domains (recommendation systems, delivery, healthcare, sales intelligence) suggests a broad interest and ability to contribute to various projects.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight leadership roles (Team Lead, Led design) and contributions to significant engineering projects, suggesting strong operational fit and potential for leadership. The detailed descriptions of complex projects imply good problem-solving and communication skills, although no direct soft skill assessment data is available.