Summary
Jai Kotia is a software engineer in machine learning with eight years of experience building large-scale ML systems across consumer, biomedical, and finance domains, currently at Snap after impactful ML work at Meta. He has driven product-facing ranking and recommendation improvements that moved millions of impressions and materially increased ad revenue, and led infrastructure and feature-selection efforts to optimize model throughput and developer productivity. His background spans end-to-end ML: deploying models in production, optimizing C++ codepaths and concurrency, and migrating analytics to distributed Spark clusters for 150% performance gains. Jai pairs academic rigor from an MS at Johns Hopkins with hands-on research in medical ML—developing predictive models for acute kidney injury and dialysis hypotension—and has built imaging pipelines and light-field prototypes for biomedical detection. Based in Sunnyvale, he blends deep engineering pragmatism with research curiosity, often finding cross-domain signals between AI in finance and biomedicine.
8 years of coding experience
7 years of employment as a software developer
Summer School Computer Science and Automation, Summer School Computer Science and Automation at Indian Institute of Science (IISc)
Johns Hopkins University
St. Xavier's Boys Academy
Bachelor of Engineering - BE Computer Science, Bachelor of Engineering - BE Computer Science at Dwarkadas J. Sanghvi College of Engineering
Science, Science at KC College
St. Mary's School ICSE