Applied Scientist, Personalization, Personalization

We are seeking an Applied Scientist to help build Amazons next-generation customer memory and personalization systems.

Are you interested in building systems that move beyond reacting to customer behavior to actually understanding and remembering it over time Our team is building Amazons customer memory layer a system that extracts curates and reasons over customer knowledge to power next-generation personalization. This includes transforming noisy unstructured signals into durable high-quality representations of customer preferences intents and life events and using them in real time to improve customer experiences.

We are part of Amazons Personalization organization a high-performing group that leverages large-scale machine learning generative AI and distributed systems to deliver highly relevant customer experiences.
We tackle challenging problems at the intersection of information extraction knowledge representation LLM reasoning and recommendation systems. Our systems operate under real-world constraints of scale latency and quality requiring careful tradeoffs between precision recall and responsiveness. This team plays a central role in defining how Amazon understands its customers and how that understanding is applied across the shopping experience.

As an Applied Scientist you will design and build ML and LLM-powered solutions for Amazons customer memory and
personalization systems. You will work on how customer knowledge is extracted validated and applied in production
systems.

You will own the end-to-end delivery of ML solutions from problem formulation and modeling to offline and online experimentation and production deployment at scale. You will deliver high-quality scalable systems that power customer-facing experiences.
You will drive work across areas such as fact extraction memory quality and lifecycle temporal reasoning and grounded personalization while navigating tradeoffs between quality latency and coverage.
You will collaborate closely with engineering and product teams to translate research into measurable customer impact.

Please visit for more information.


- Knowledge of computer science fundamentals in data structures algorithm design and problem solving
- Excellent coding and design skills proficiency with programming languages such as Java or Python
- Several publications at top-tier peer-reviewed research conferences or journals
- Strong communication and collaboration skills
- PhD or a Masters degree and experience in CS CE ML or related field research

- Experience in building and launching deep learning and machine learning models for business applications
- Solid knowledge of big data and cloud technologies (e.g. Spark AWS etc.)
- Experience with information retrieval recommender systems natural language processing and/or personalization algorithms
- Publications at top Web Machine Learning Natural Language Processing conferences such as KDD ICML NeurIPS ACL EMNLP etc.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.