FBA AI Science and Analytics accelerates Amazon’s AI-native transformation for Fulfillment by Amazon by building, integrating, and scaling AI-powered data and science products and seller-facing experiences that drive operational efficiency and growth. We study seller behavior, design policies and incentives, and ship data-driven products that help third-party sellers grow topline revenue and reduce costs at Amazon scale. Our work sits at the intersection of machine learning, statistics, economics, operations research, and GenAI/LLMs.

We are seeking a Senior Applied Scientist to apply GenAI to a high-visibility problem: building next-generation multi-agent systems that interact with millions of sellers and guide them through their toughest challenges at scale. You will own end-to-end solutions spanning supervised and unsupervised learning, recommendation systems, statistical learning, large language models, and reinforced learning. The goal is to make AI a native layer in every seller decision, delivering actionable insights in minutes rather than days. You will shape end-to-end experiences across high-frequency seller workflows, including inventory optimization, inbound efficiency, defect reductions, reimbursements, and capacity planning. The role reports to senior business leaders and collaborates with fellow scientists, engineers, and product teams to launch production-grade, agentic capabilities.

Key responsibilities: - Design, build, and deploy GenAI architectures end-to-end for FBA. - Apply state-of-the-art ML and GenAI to solve diverse business problems across selle

FBA AI Science and Analytics accelerates Amazon’s AI-native transformation for Fulfillment by Amazon by building, integrating, and scaling AI-powered data and science products and seller-facing experiences that drive operational efficiency and growth. We study seller behavior, design policies and incentives, and ship data-driven products that help third-party sellers grow topline revenue and reduce costs at Amazon scale. Our work sits at the intersection of machine learning, statistics, economics, operations research, and GenAI/LLMs.

We are seeking a Senior Applied Scientist to apply GenAI to a high-visibility problem: building next-generation multi-agent systems that interact with millions of sellers and guide them through their toughest challenges at scale. You will own end-to-end solutions spanning supervised and unsupervised learning, recommendation systems, statistical learning, large language models, and reinforced learning. The goal is to make AI a native layer in every seller decision, delivering actionable insights in minutes rather than days. You will shape end-to-end experiences across high-frequency seller workflows, including inventory optimization, inbound efficiency, defect reductions, reimbursements, and capacity planning. The role reports to senior business leaders and collaborates with fellow scientists, engineers, and product teams to launch production-grade, agentic capabilities.

Key responsibilities: - Design, build, and deploy GenAI architectures end-to-end for FBA. - Apply state-of-the-art ML and GenAI to solve diverse business problems across selle