Summary
Aneesh Shetty is a Deep Learning Engineer with 8 years of experience applying LLMs, reinforcement learning, and graph neural networks to real-world systems across industry and academia. Currently at AWS Annapurna Labs, he blends production engineering with applied research, having previously built core PDF and async APIs at Adobe and scalable benchmarking and scheduler systems at Amazon. His research at UT Austin spans interpretable recommender systems, healthcare recommendations, and provable RL policies for social navigation, reflecting a rare mix of theory and deployment. Early work on India’s Aarogya Setu contact-tracing model helped trace millions and informed privacy-conscious, deployable designs—an example of impact at national scale. He holds a CS MS from UT Austin and a BTech from IIT Bombay, and is comfortable moving between C++/V8 bindings, deep learning models, and cloud-native infrastructure. Colleagues value him for shipping rigorous, production-ready ML systems that arise from strong formal foundations.
8 years of coding experience
2 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at The University of Texas at Austin
Indian Institute of Technology Bombay
English, Hindi