Senior Applied Scientist, Catalog System Services Science
Core
Building state-of-the-art GenAI algorithms and models to enrich product information and infer relationships across billions of products for Amazon's search and browse experiences.
Role type
Senior Applied Scientist (GenAI & Multimodal)
Builds
Next-generation agentic shopping experiences and product catalog services
Domain
E-commerce, GenAI, Multimodal Learning
Deliverable
production ML models
Required skills
GenAI, multimodal learning, large-scale information retrieval, explainable AI, end-to-end ML pipeline ownership, research roadmap definition, mentorship
Preferred skills
LLMs, foundation models, large-scale deep learning systems, multimodal LLMs, post-training techniques, top-tier conference publications
Technologies
Java, C++, Python, neural deep learning methods
Responsibilities
Formulate novel research problems at the intersection of GenAI and large-scale information retrieval; Design and implement leading models leveraging frontier models and agentic architectures; Pioneer explainable AI methodologies for production systems; Own end-to-end ML pipelines from ideation to deployment; Define research roadmaps aligned with business priorities; Mentor peer scientists and engineers; Represent the team in the broader science community
Seniority
Senior, hands-on IC with mentorship
