Summary
Revanth Madamala is a Machine Learning Engineer and AI researcher with 9 years of experience building production-grade ML systems for ranking, recommendations, GenAI, and NLP across Meta, TikTok, LexisNexis, Autodesk and startups. He combines hands-on engineering—delivering measurable gains like a 32% uplift in pricing prediction and large improvements in recommendation relevance—with research depth (15+ papers, multiple patents, and 3 books) to translate novel models into reliable, scalable services. At Meta he focuses on high-throughput ads ranking and fairness, while prior roles span e-commerce MixRank, RAG-based legal LLM pipelines that cut hallucinations, and graph-based procedural knowledge research from USC. Revanth mentors engineers and researchers, helping them break into top-tier AI teams and convert research into product impact, and he’s active judging industry AI awards—an indicator of his domain recognition beyond hands-on delivery. An underappreciated strength: he routinely pairs architecture changes (sparse modules, dynamic routing) with practical deployment pipelines to close the gap between SOTA research and production constraints.
9 years of coding experience
5 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at University of Southern California
Bachelor of Technology - BTech, Computer Engineering( Dept of CSE), Bachelor of Technology - BTech, Computer Engineering( Dept of CSE) at Indian Institute of Information Technology Design & Manufacturing, Kurnool
Telugu, English, Hindi