Sr. Applied Scientist, Prime AI/ML Science

About the role

Join our team of Scientists developing models to understand and predict customer behavior, optimize the customer experience for Amazon Prime, and drive impact at scale for millions of customers. This role involves modeling customer behavior, assessing the long-term value of the Prime membership program, and creating personalized frameworks for content and subscription optimization.

You will tackle scientific and technical challenges such as optimizing GenAI/LLM solutions for Prime personalization, building foundation models, ensuring global scalability, addressing cold-start problems, accelerated experimentation, modeling short/long-term goals, and multi-step optimization leading to reinforcement learning of the customer journey. Techniques include GenAI/LLMs, supervised/semi-supervised learning, deep learning, transformer architectures, causal econometric modeling, and reinforcement learning.

As the central science team within Prime, you will collaborate directly with product owners, contribute to scientific research, and help shape a strong publication and patent record. You will also work with cutting-edge ML technologies and infrastructure, including AWS (EMR/Spark, Sagemaker, DynamoDB, S3, ClaudeCode), advanced AI/ML algorithms, and statistical modeling techniques.

Responsibilities

• Stay abreast of current literature in the field and advance/build novel science solutions leveraging state-of-the-art (SoTA) techniques.
• Build and develop AI/ML models and supporting infrastructure at terabyte scale in coordination with software engineering teams.
• Leverage deep learning and GenAI solutions for building foundation models and personalized optimization.
• 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 amounts of Amazon’s historical business data to automate and optimize key processes.
• Work closely with business teams to understand problem spaces, identify opportunities, and formulate problems.
• Use AI, machine learning, data mining, and statistical techniques to create actionable, meaningful, and scalable solutions for business problems.
• Design, develop, and evaluate highly innovative models and statistical approaches to understand and predict customer behavior.

Requirements

• 3+ years of experience building machine learning models for business applications.
• PhD or Master’s degree with 6+ years of applied research experience.
• Experience programming in Java, C++, Python, or a related language.
• Experience with neural deep learning methods and machine learning.

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLlib, MxNet, TensorFlow, NumPy, or SciPy.
• Experience with large-scale distributed systems such as Hadoop or Spark.