Summary
Anurag Shenoy is a Machine Learning Engineer and researcher with a decade of experience and a MS in Computer Science from the University of Florida, specializing in NLP, MLOps, and scalable backend systems. He has led end-to-end ML projects—from training large models on supercomputing infrastructure and optimizing LLM inference to production deployments with Docker, Kubernetes, TensorFlow Serving and gRPC. His work spans applied research (co-authoring AI papers and decoding attention from live EEG) and high-impact product engineering (building agentic chatbots, 100+ secure REST APIs, and a 400% boost in annotation throughput). Notably, he reduced model tuning times by 75% through pipeline caching/prefetching and doubled inference capacity via production optimizations. Comfortable in cross-functional teams, he seeks roles that blend research rigor with product-driven Generative AI and LLM system design.
9 years of coding experience
3 years of employment as a software developer
Bachelor of Technology, Electrical, Electronics and Communications Engineering, Bachelor of Technology, Electrical, Electronics and Communications Engineering at SIES Graduate School Of Technology
Master of Science - MS, Computer Science, 3.76, Master of Science - MS, Computer Science, 3.76 at University of Florida