The GRAISE team (Grocery, Retail & In-Store Experience) within World Wide Grocery Store Tech (WWGST) builds foundational AI and machine learning systems that power Amazon's in-store grocery technologies. We develop domain-specific models that solve uniquely complex challenges in grocery — from smart shopping carts and inventory intelligence to personalization and store operations. Our mission is to create technology which makes grocery shopping more convenient, economical, personalized, and enjoyable for customers while empowering retailers with operational efficiency
- 2+ years of solving business problems through machine learning, data mining and statistical algorithms experience
- Experience in designing experiments and statistical analysis of results
- Experience programming in Java, C++, Python or related language
- Experience working with large sets of data and deriving practical insights
- 2+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience
- Experience developing and evaluating data annotation and data quality metrics
- Demonstrated ability to take a model from research prototype to production deployment — including performance profiling, latency optimization, and working within serving infrastructure constraints
- Track record of clearly documenting experiments, writing technical design documents, and communicating results to cross-functional partners
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