Machine Learning Engineer II, Search Science and Data Infrastructure

Amazon Search creates powerful, customer-focused product search solutions and technologies. As a Machine Learning Engineer II in the Search Science Data Infrastructure team, you will be responsible for delivering high-quality ML model training data and providing seamless access to ML artifacts through federated Feature Store infrastructure.

Key responsibilities include:

• Leading development of services and infrastructure at the intersection of machine learning, big data, and distributed systems.
• Managing machine learning lifecycle and operations using AWS AI services, DL compute resources, and core search backend services.
• Building scalable data-intensive infrastructure to process huge amounts of logs, catalogs, transactional data, and telemetry signals.
• Working with partners on data experimentation to advance Amazon product search across all geographic regions.
• Designing, coding, and deploying big data and machine learning services that support the world's largest product search engine.
• Possessing expert knowledge in performance, large-scale distributed system scalability, system architecture, and engineering best practices.
• Obsessing over operational excellence, evaluating system performance, security, designing system metrics, and driving quality improvements.

This role offers the opportunity to work on cutting-edge technology in a dynamic environment, contributing to the foundation of Amazon's search R&D processes. You'll be part of a team that powers various aspects of Amazon's search functionality, including search suggestions, query understanding, spelling, search result ranking, and personalization.

The position is located in downtown Palo Alto, offering a vibrant work environment with easy access to shops, restaurants, and public transportation. Join Amazon Search and help shape the future of e-commerce search technology!