Guruprasad Nayak

About Guruprasad Nayak

I lead ads in Rufus - Amazon’s agentic AI powered shopping assistant. I have 13+ years of experience in data science and machine learning, including 6.5+ years of industry experience with deep technical expertise in generative AI, agentic architectures, autoML, time series forecasting and semi-supervised learning - supported by 20+ publications and 300+ citations. Regular contributor and reviewer for top ML and AI conferences - my Google scholar profile: & hl=enI enjoy collaborating with diverse cross-functional teams, learning from different perspectives and experiences, and using the latest in AI research to solve pressing business problems.Professional Highlights I lead ads in Rufus - Amazon’s agentic AI powered shopping assistant. Launched 3 new adexperiences in Amazon’s shopping assistant (Rufus)- product recommendations, brand curated productcollections and sponsored prompts (AI-generated contextualized clickable ads), generating $ XX MM USD inannualized revenue for Amazon ads. Developed 3 LLM-based functionalities over 3 years for Amazon Q (Sagemaker Canvas), leading to 3X% YoY revenue growth and $XXM ARR as of 2025. In particular, the GenAI launches helped increase the end-to-end workflow completion within Sagemaker Canvas, increasing the ratio of completed jobs from 77% to 92%. Designed, developed, deployed and maintained the evaluation system for the advertising inventory forecasting tool on Amazon advertising’s demand side platform. This was a key component of the bi-weekly business reviews presented to the org-leadership and other product stakeholders. Worked with NASA Research Center to build models for identifying rare classes when there is a complete absence of expert labels. Applied these techniques on spatio-temporal data from satellites and produced a more reliable and comprehensive burned area database compared to the state-of-art NASA productNOTE: opinions shared on LinkedIn are my own and do not express the opinions and views of my employer.

Experience

1. Applied Science Manager

   Amazon

   Jul 2025 — Present · Seattle, WA, US

   I lead a team of 6+ talented scientists and engineers responsible for building Gen-AI driven conversational ad experiences on Amazon (search, Rufus, product detail pages).• Work on LLM post training, reasoning, personalization and agentic architectures for shopping and ads• Delivered 5+ launches covering Rufus and Amazon Search resulting in $XX MM USD in annualized revenue for Amazon ads.

Education

• Indian Institute of Technology, Kanpur

  Bachelor’s Degree, Computer Science

  2013

• University of Minnesota

  Doctor of Philosophy (Ph.D.), Computer Science (Machine Learning)

  2019