Applied Scientist II - Personalization, Customer Intent Science

Are you interested in big data, Machine Learning, and building recommendation services using Generative AI? If so, Amazon"s Personalization team might be the right place for you.

Key job responsibilities

• Use AI and machine learning to create scalable solutions for business problems.
• Analyze and extract relevant information from large amounts of Amazon"s historical business data to help automate and optimize key processes.
• Design, develop and evaluate highly scalable models for predictive learning.
• Work closely with software engineering teams to drive model implementations and new feature creations.
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
• Research and implement novel machine learning and statistical approaches
• Review peer work and provide feedback

A day in the life

You are an Applied Scientist who loves big data and passionate about improving customer shopping experience by inventing and applying state-of-art technologies (e.g., LLMs/SLMs, Machine Learning, Natural Language Processing, and Computer Vision) to build the next-generation product recommendation engine for Amazon. You have an entrepreneurial spirit, know how to deliver, are deeply technical and highly innovative. You work closely with software engineers to put algorithms into production. You also work in partnership with teams across Amazon to create enormous benefits for our customers.

About the team

We are part of Amazon's Personalization organization, a high-performing group with a huge impact on hundreds of millions of customers, innovating at the intersection of customer experience, machine learning, and large-scale distributed systems. We run global experiments and our work has revolutionized e-commerce with features such as "Compare with similar items", "Keep Shopping For", "Customers who bought this item also bought", and, "Frequently bought together" among others.