Amazon Rufus Experience Science is seeking a highly motivated Scientist who is passionate about building next-generation shopping experiences. In this role, you will help create conversational shopping journeys where customers can express any shopping needdiscovering products, comparing options, finding inspiration, or resolving post-purchase issues. You will collaborate closely with a multidisciplinary team of scientists, engineers, product managers, and designers to deliver these experiences across multiple Rufus customer-facing features. You will thrive in this role if you enjoy bringing latest research into everyday lifeboth for customers and for yourself. Theres nothing quite like realizing that a model you deployed yesterday is already improving your own shopping experience today. You will work side by side with scientists and engineers in a fast-paced environment, driving rapid model development and experimentation. Youll also have access to Amazons rich datasets, AW - Ss massive computational resources, and a network of world-class science and engineering leaders across the company. Key job responsibilities. Execute the science vision and roadmap. Develop data-driven solutions for the real-world, large scale problems. Deliver and maintain software and models in the production environment. Collaborate cross-functionally between product, design, and engineering. Basic Qualifications- 3 years of building models for business application experience- PhD, or Master's degree and 4 years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C , Python or related language- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning. Preferred Qualifications- Knowledge of architectural concepts and algorithms, schedule tradeoffs and new opportunities with technical team members- PhD in computer science, electrical engineering, or related field- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)