Applied Scientist II, Search Query Understanding
Core
Develop and optimize Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) to understand user shopping missions and enhance the Amazon search engine into a shopping engine.
Role type
Senior Applied Scientist (Search Query Understanding)
Builds
Scalable ML models for search query understanding and shopping mission analysis
Domain
E-commerce, Search, Large Language Models (LLMs), Retrieval Augmented Generation (RAG)
Deliverable
production ML models
Required skills
Machine Learning, Artificial Intelligence, Large Language Models (LLMs), Retrieval Augmented Generation (RAG), post-training of foundation models, LLM inference optimization, algorithms and data structures, numerical optimization, data mining, parallel and distributed computing, high-performance computing, data management, software engineering best practices
Preferred skills
Unix/Linux, professional software development
Technologies
Java, C++, Python
Responsibilities
Collaborate with cross-functional teams to identify requirements for ML model development; Design and implement scalable ML models to process large datasets; Lead management and experiments of ML models at scale; Serve as a technical lead and liaison for ML projects
Seniority
Senior, hands-on IC
