Amazon is looking for creative Applied Scientists to tackle some of the most interesting problems in Artificial Intelligence (AI), natural language processing (NLP), knowledge graph curation, search, recommendation and related areas with our Amazon Books team. At Amazon Books we believe that reading is essential for a healthy society. As such, we aim to inspire readers by making it easy to

If you are looking for an opportunity to solve deep technical problems and build innovative solutions in a fast-paced environment working within a smart and passionate team, this might be the role for you. You will develop and implement novel algorithms, agentic systems and modeling techniques to advance the state-of-the-art in technology areas at the intersection of AI, LLMs, NLP, search, and deep learning. You will innovate at scale, help move the needle for research in these exciting areas and build state-of-the-art technologies that enable delightful experiences for hundreds of millions of people.

Key job responsibilities
In this role you will:
- Work collaboratively with other scientists and developers to design and implement scalable and reliable pipelines for ensuring our vast knowledge base of books meets the highest levels of accuracy and is aligned with how customers think about books;
- set the scientific roadmap needed to sustain state-of-the-art quality and efficiency. Stay up-to-date with the latest technologies and adopt the most appropriate long-term solution to a variety of use cases.
- set the standard for science rigor and quality, deal with ambiguity and competing objectives, and mentor other members to achieve their career growth potential.
- Drive scalable solutions: from understanding the customer and business needs, to prototyping, production testing and through engineering directly to production.

A day in the life
Day-to-day work varies, but on a typical day you will:
- run (or supervise) experiments. Depending on the stage or project, this may involve designing the experiments, collecting data, training models, prompt/spec engineering/optimization, error analysis, online system analysis, etc.
- drive decisions by interpreting and communicating experimental results with stakeholders (managers, subject matter experts, other scientists, and engineers) and seeking/listening to their feedback.
- strategic thinking: review results, identify trends and what step-changes are needed.

You'll contribute to regular meetings, activities and conferences with the wider science team, organization as well as internal and external communities.

About the team
The team consists of a collaborative group of scientists, product leaders, and dedicated engineering teams. Our aim is to maintain the world's most accurate and descriptive set of books metadata, where every title in our catalog is uniquely characterized via a set of high-quality, concise attributes. We believe this is a foundational capacity for any bookstore. We work with sister teams to leverage our systems to drive a diverse array of customer experiences, owned both by ourselves and others, that enable customers to easily identify their ideal next read.