Applied Scientist, Amazon Selection and Catalog Systems (ASCS)
Core
Build state-of-the-art algorithms and GenAI models to infer product identities and relationships at billion-product scale for Amazon's search and browse experiences.
Role type
Senior Applied Scientist (GenAI, Multimodal Learning)
Builds
Next-generation agentic shopping experiences and product catalog understanding systems
Domain
E-commerce, Generative AI, Multimodal AI
Deliverable
production ML models
Required skills
GenAI, Visual Language Models (VLMs), multimodal learning, large-scale information retrieval, explainable AI, end-to-end ML pipeline ownership, research roadmap definition, technical mentorship
Preferred skills
PhD in CS/CE/ML, publications at top-tier conferences, proven track record of applying ML to complex business problems
Technologies
Java, C++, Python
Responsibilities
Formulate novel research problems at the intersection of GenAI and information retrieval; Design and implement leading models leveraging VLMs and foundation models; 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 responsibilities