GenAI & Multimodal Catalog Scientist

Amazon Inc.; Seattle, Northern (WA, KY); Hybrid; USD 143,000 - 193,000; Full time

Benefits offered by this job

RSUs

Health insurance

401(k)

Job summary

Amazon Inc. is seeking an innovative applied scientist for the Catalog Systems Services Science team in Seattle. You will partner with tech and business leaders to build state-of-the-art GenAI models and services, enabling better product catalog understanding and agentic shopping experiences at scale.

You will own end-to-end ML pipelines, publish findings, and contribute to advancing GenAI, VLMs, and explainable AI methodologies in production environments serving millions of customers.

Qualifications

• PhD or Master’s degree with 4+ years CS/ML experience.
• Experience programming in Java, C++, Python.
• 2+ years building ML models or developing algorithms for business applications.
• Prior experience in LLMs or large-scale deep learning systems.

Responsibilities

• Formulate research problems at the intersection of GenAI, multimodal learning, and large-scale information retrieval.
• Design and implement models leveraging frontier models and agentic architectures to enrich catalog information at billion-product scale.
• Pioneer explainable AI methodologies balancing performance with production scalability for systems affecting millions of daily decisions.
• Own end-to-end ML pipelines from research ideation to production deployment across petabytes of multimodal data.
• Represent the team in the broader science community through publications and tech talks.

Skills

PhD/Master's degree plus 4+ years CS/

Programming in Java/C++/Python

ML model development

LLMs / large-scale DL

Education

PhD/ Master’s in CS/ML

Tools

Java

C++

Python

Job description

Amazon Inc. is seeking an innovative applied scientist for the Catalog Systems Services Science team in Seattle. You will partner with tech and business leaders to build state-of-the-art GenAI models and services, enabling better product catalog understanding and agentic shopping experiences at scale.

You will own end-to-end ML pipelines, publish findings, and contribute to advancing GenAI, VLMs, and explainable AI methodologies in production environments serving millions of customers.