Applied Scientist, Amazon Prime, Prime AI/ML Science

Interested in modeling and understanding customer behavior through machine learning, artificial intelligence, and data mining over TB scale data with huge business impact on millions of customers? Join our team of Scientists and Engineers developing models to predict customer behavior and optimize the customer experience with Amazon Prime. This includes identifying who our customers are, modeling customer behavior, and creating personalization systems to optimize the experience. As an ML expert, you will partner directly with product owners to intake, build, and directly apply your modeling solutions.

There are numerous scientific and technical challenges you will get to tackle in this role, such as global scalability of models, combinatorial optimization, cold start problem, accelerated experimentation, short/long term goals modeling, GenAI based content creation, foundation modeling, and multi-step optimization leading to reinforcement learning of the customer journey. We employ techniques from GenAI, LLMs, deep learning, supervised learning, bandits, optimization, and RL.

As the central science team within Prime, our expertise gets routinely called upon to weigh in on a variety of topics. We also emphasize the need and value of scientific research and have developed a strong publication and patent record (internally/externally) which you will be a part of.

You will also utilize and be exposed to the latest in AI/ML technologies and infrastructure: AWS technologies (EMR/Spark, Redshift, Sagemaker, DynamoDB, S3, ...), various AI/ML algorithms and techniques (GenAI, LLMs, transformers, sequential models, Neural Networks, supervised/unsupervised/semi-supervised/reinforcement learning), and statistical modeling techniques.

Major responsibilities

• Build and develop AI and machine learning models and supporting infrastructure at TB scale, in coordination with software engineering teams.
• Leverage GenAI, LLMs, deep learning, reinforcement learning for building production AI/ML systems
• Develop backtesting/offline policy estimation tools and integrate with reporting systems.
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
• Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key processes.
• Work closely with the business to understand their problem space, identify the opportunities and formulate the problems.
• Use AI, machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions for the business problems.
• Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems.