Summary
Shalin Shah is a founding scientist and machine learning engineer with eight years of experience building production-grade AI systems across startups and large enterprises like Target and Microsoft. He holds master’s degrees in Applied and Computational Mathematics (JHU) and Computer Science (USC), blending rigorous theoretical foundations in stochastic processes and ML theory with practical expertise in programming languages, algorithms, and distributed systems. At Anvai AI he focuses on LLMs and generative AI—fine-tuning, prompt engineering, RAG, and knowledge-graph-driven question answering for free-form financial queries—bringing structure to unstructured text. Previously he led ML and deep learning efforts for recommender systems, NLP, and vision at Target and worked on search relevance and ranking at Bing. He is comfortable moving between research and productization, combining statistical modeling and computational linguistics to solve real-world problems. Based in Sunnyvale, he maintains an active technical presence (shah314.github.io) that reflects both research rigor and product-first engineering.
8 years of coding experience
14 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 Engineering - BE, Electrical Engineering, Bachelor of Engineering - BE, Electrical Engineering at Gujarat University
Master of Science - MS, Applied and Computational Mathematics, Master of Science - MS, Applied and Computational Mathematics at Johns Hopkins Whiting School of Engineering
English, Hindi, Gujarati