Applied Scientist: GenAI & Multimodal Catalog Systems

Amazon Science; New York (NY); On-site; USD 150,000 - 190,000; Full time

Job summary

Amazon Science is seeking an innovative applied scientist to advance GenAI and multimodal AI for the world’s largest product catalog. You will collaborate with technology and business leaders to build state‑of‑the‑art algorithms and services, inferring product relationships at scale and deploying ideas across millions of customers.

You will innovate on agentic shopping experiences, publish findings, and mentor teams while tackling high‑impact research challenges across images and text in a

Qualifications

• PhD, or Master’s degree and 4+ years of CS, CE, ML or related field experience.
• Experience programming in Java, C++, Python or related language.
• Publications in top-tier conferences or journals preferred.
• Proven track record applying ML solutions to complex problems in business, science, or engineering.

Responsibilities

• Formulate novel research problems at the intersection of GenAI, multimodal learning, and IR—turn business challenges into tractable research.
• Design and implement models leveraging VLMs, foundation models, and agentic architectures for product identity and catalog understanding at scale.
• Pioneer explainable AI methods balancing performance and production scalability.
• Own end-to-end ML pipelines from research ideation to production deployment over petabytes of data.
• Define research roadmaps aligned with business priorities and product improvements.
• Mentor scientists and engineers on ML techniques, experimental design, and rigor.

Skills

GenAI

VLMs

Multimodal AI

Research design

Mentoring

Education

PhD

Master's degree

Tools

Java

C++

Python

Job description

Amazon Science is seeking an innovative applied scientist to advance GenAI and multimodal AI for the world’s largest product catalog. You will collaborate with technology and business leaders to build state‑of‑the‑art algorithms and services, inferring product relationships at scale and deploying ideas across millions of customers.

You will innovate on agentic shopping experiences, publish findings, and mentor teams while tackling high‑impact research challenges across images and text in a