Sr. Applied Scientist, Prime AI/ML Science

About the role

Join our team of Scientists developing models to understand and optimize customer behavior and experience with Amazon Prime. This includes analyzing customer identity, long-term value of the Prime membership program, and creating personalized frameworks for content and subscription optimization. You will partner directly with product owners to build and apply modeling solutions, tackling challenges such as GenAI/LLM optimization for personalization, global scalability, combinatorial optimization, cold start problems, and reinforcement learning of the customer journey.

We employ techniques from GenAI/LLMs, supervised/semi-supervised learning, deep learning, transformer architectures, causal econometric modeling, and reinforcement learning. As the central science team within Prime, we contribute to a variety of topics and maintain a strong publication and patent record. You will work with cutting-edge ML technologies and infrastructure, including AWS (EMR/Spark, SageMaker, DynamoDB, S3, ClaudeCode), and stay current with advancements in the field.

Responsibilities

• Stay abreast of current literature and build novel science solutions leveraging state-of-the-art (SoTA) techniques.
• Develop AI/ML models and supporting infrastructure at terabyte scale in coordination with software engineering teams.
• Leverage deep learning and GenAI solutions to build foundation models and personalized optimization frameworks.
• Develop offline policy estimation tools and integrate them with measurement systems and econometric models.
• Establish scalable, efficient, and automated processes for large-scale data analyses, science development, validation, and model implementation.
• Analyze and extract relevant information from large volumes of Amazon’s historical business data to automate and optimize key processes.
• Collaborate closely with business teams to understand problem spaces, identify opportunities, and formulate actionable solutions.
• Use AI, machine learning, data mining, and statistical techniques to create scalable solutions for business problems.
• Design, develop, and evaluate innovative models and statistical approaches to predict customer behavior and solve business challenges.

Requirements

• Expertise in GenAI/LLMs, supervised/semi-supervised learning, deep learning, transformer architectures, and reinforcement learning.
• Experience with AWS technologies (e.g., EMR/Spark, SageMaker, DynamoDB, S3).
• Ability to build and deploy models at terabyte scale.
• Strong background in statistical modeling and data mining.
• Experience working with large-scale historical business data.
• Track record of advancing scientific research, including publications and patents.
• Collaborative mindset with the ability to work closely with product owners and engineering teams.