Sr Manager, Applied Science, Search

Saved job description

Search's mission is to connect customers worldwide to Amazon's vast selection, helping them quickly evaluate their options and find what they need while also inspiring exploration and discovery. We are working on delivering a search results page that understands the full spectrum of customer intent, from open-ended discovery to spearfishing, and assembles itself accordingly with every part of the page reflecting the customer's specific context, query, intent, preferences and real-time browsing signals adapting as their mission evolves. We are looking for a Senior Applied Science Manager to lead the development of leading AI/ML solutions that power intelligent, adaptive search experiences for hundreds of millions of customers worldwide. This is a rare opportunity to shape the science strategy for one of Amazon's most impactful programs at the intersection of massive-scale behavioral data, real-time decision systems, and generative AI. You will lead cross-functional teams of scientists, engineers, and product managers to integrate LLMs into existing search systems while delivering low-latency solutions that serve billions of daily interactions.

Key job responsibilities

A Sr. Manager, Applied Science in this role develops a comprehensive science strategy that brings deep expertise in page optimization and faceout optimization to drive adaptive search experiences, working with Principal Scientists to innovate on LLM integration and real-time personalization. You translate this strategy into measurable business impact by leading cross-functional teams through experimentation, ensuring every component of the search results page reflects customer intent and context while maintaining strict latency requirements.

Requirements: - 10+ years of building large-scale machine learning and AI solutions at Internet scale experience

- Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)

- Experience building large-scale machine learning and AI solutions at Internet scale

- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives

- Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track