Applied Science Manager - Web Search/Retrieval/Ranking, AGI Info - Web Information Systems

Amazon • Sunnyvale, CA

4d

About The Position

Help shape the future of artificial intelligence by leading breakthrough innovations in web search and Retrieval Augmented Generation at Amazon AGI. We're seeking an exceptional Applied Science Manager to drive the development of next-generation search capabilities to improve agentic applications across Amazon. Your work will directly influence the next generation of Amazon's search and AI systems, improving how millions of users interact with our platforms through more intelligent and efficient information retrieval systems.

Requirements

• 3+ years of scientists or machine learning engineers management experience
• Knowledge of ML, NLP, Information Retrieval and Analytics
• Experience hiring and growing top talent
• Experience building machine learning models or developing algorithms for business application
• Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
• Experience developing large scale search systems

Nice To Haves

• demonstrated experience in Information Retrieval Systems (learned sparse and dense retrieval, efficient sparse and ANN indexing, learning-to-rank models, content understanding/information extraction, etc.) and Large Language Models (Retrieval-augmented generation (RAG) architectures, post-training techniques, inference optimization techniques, etc.)

Responsibilities

• lead a team of scientists to improve our web search capabilities and drive key improvements across multiple agentic systems across Amazon
• developing novel retrieval and ranking models to improve search, incorporating multiple objectives (e.g. relevance and trustworthiness), and partnering closely with engineering to improve model performance
• improve content and query understanding models to deliver improved signal to retrieval and ranking models
• partner closely with content acquisition and customer teams to ensure our dependencies are met and we’re delivering value to the end customers, enhancing information grounding for LLMs
• develop a science roadmap, including publication opportunities and how we can accelerate delivery of customer impact
• coach and develop the team, hire, and hold the bar on scientific rigor throughout the team

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees