Summary
Rohit Ramesh is an Applied Scientist with nine years of hands-on experience building ML and DL systems for recommendation, ranking, and video-shopping experiences at companies like Amazon, StockX, and DocuSign. He combines practical production skills—SageMaker deployments, Databricks/PySpark ETL, OpenSearch k-NN stores, and CI/CD—with research-minded expertise in game theory and mechanism design, a rare intersection he actively explores. At StockX and Amazon he improved key engagement and conversion metrics via deep & wide networks, CLIP/transformer embeddings, and scalable feature pipelines, and has delivered measurable A/B test wins. His background includes academic research into human reasoning in game-theoretic settings and teaching mathematical foundations, highlighting strong theoretical grounding alongside product impact. Based in San Francisco, he brings both startup agility and enterprise rigor to ML lifecycle problems, with a demonstrated knack for turning CV and NLP innovations into low-latency, production-ready services.
9 years of coding experience
6 years of employment as a software developer
B.Tech, Computer and Communication Engg., 8.37 CGPA, B.Tech, Computer and Communication Engg., 8.37 CGPA at Manipal Institute of Technology
Master's, Computer Science, 4.0, Master's, Computer Science, 4.0 at University of Illinois at Chicago
High School, PERCENTAGE:88.4%, High School, PERCENTAGE:88.4% at Maharishi Vidya Mandir
CGPA:10, CGPA:10 at D.A.V Public School
Tamil, English, Hindi, Telugu