Machine Learning Engineer, JP Science and Data

Amazon's JP Science and Data team is seeking a Machine Learning Engineer to architect and implement end-to-end machine learning systems that scale across Amazon's largest vendors. This role combines strong software engineering principles with machine learning expertise to build robust, production-grade ML platforms and pipelines supporting advanced analytics and machine learning models for eCommerce partners. You'll work directly with Applied Scientists, Software Development Engineers, Data/BI Engineers, and Product Managers to drive Amazon's new generation of Paid Services.

The position offers exposure to cutting-edge areas including causal inference, representation learning, anomaly detection, forecasting, and LLMs. As part of the JP Science and Data team, you'll collaborate with scientists, engineers, and product managers worldwide. The team emphasizes continuous learning and aims to be the primary science team for vendor solutions globally.

The ideal candidate brings strong software engineering and machine learning systems background, with proven experience in ML lifecycle management and infrastructure development. You'll be responsible for productionizing ML models, building scalable infrastructure, and implementing ML-ready data pipelines while working closely with vendors and internal partners to shape future capabilities.

This role offers the opportunity to work on high-impact projects that directly influence Amazon's vendor partnerships while being part of a collaborative team that values continuous learning and technical excellence. The position combines technical depth in machine learning engineering with the scale and complexity of Amazon's eCommerce ecosystem.