Summary
Rupinder Khandpur is a Senior Machine Learning Engineer at Meta with a decade of experience building production ML and recommender systems for Ads, specializing in model iteration, evaluation, experimentation, and platform automation. He previously led AI/ML as Director at Moody’s Analytics Accelerator, delivering NLP and IR products for credit-risk intelligence, adverse media detection, and compliance using unstructured data. His academic background—Ph.D. in Computer Science (Virginia Tech) and an MS in Computational Biology (Carnegie Mellon)—underpins research strengths in event detection, forecasting, dynamic query expansion, and OSINT from news and social media. Practically fluent across the ML lifecycle, he focuses on infra-aware optimization, embedding footprint tradeoffs, feature utility, and agentic workflows for model fine-tuning. Notable past work includes core contributions to EMBERS, an IARPA project forecasting societal events, highlighting a rare blend of high-impact research and production engineering. Based in New York, he brings both product-facing delivery experience and deep research instincts to scale robust ML systems.
10 years of coding experience
15 years of employment as a software developer
PhD Computer Science, PhD Computer Science at Virginia Tech
MS Computational Biology, MS Computational Biology at Carnegie Mellon University
Bachelor of Technology Biotechnology, Bachelor of Technology Biotechnology at Amity Institute of Biotechnology