Join PayPal's Consumer Product Catalog and Consumer Search team and help build the next generation of product discovery for millions of global shoppers. We own the backend and data infrastructure that powers search, recommendations, and catalog knowledge at global scale. As a Machine Learning Engineer, you'll contribute to key components of the product search stack - including indexing pipelines, and query-time services that deliver fast and relevant search results. You'll collaborate closely with backend engineers and catalog data teams to enable intelligent, contextual, and scalable search capabilities. We're looking for motivated and collaborative engineers who thrive on solving complex problems in large-scale search systems. You will work on challenges such as query and document understanding, product entity modeling and enrichment, taxonomy structuring, retrieval and ranking algorithms, and search quality evaluation. You will build models that enhance search relevance and ranking, delivering highly relevant results to users across the PayPal ecosystem. The ideal candidate brings strong experience in machine learning systems, takes ownership of the project from research and prototyping to production deployment, and is eager to shape modern, AI-powered search experiences.