Applied Scientist – Customer Memory & Personalization

About the role

Amazon is building a next‑generation customer memory layer that extracts, curates, and reasons over customer knowledge to power personalized experiences. As an Applied Scientist you will create machine‑learning and large‑language‑model solutions that transform noisy signals into durable representations of preferences, intents, and life events.

Key responsibilities

• Design and implement ML/LLM‑powered pipelines for extracting, validating, and applying customer knowledge.
• Own end‑to‑end delivery of models, from problem formulation through offline/online experimentation to production deployment at scale.
• Drive research and engineering work across fact extraction, memory quality, temporal reasoning, and grounded personalization.
• Balance trade‑offs among precision, recall, latency, and coverage under real‑world constraints.
• Collaborate closely with engineering and product teams to translate research into measurable customer impact.

Required profile

• Strong programming skills in C/C++, Python, Java or Perl.
• Track record of patents or publications at top‑tier peer‑reviewed conferences or journals.
• Experience communicating technical concepts clearly to leadership and cross‑functional stakeholders.
• Experience building and launching deep learning and machine‑learning models for business applications.

Required skills

• Python, C/C++, Java, Perl
• Deep learning and machine‑learning model development
• Big data and cloud technologies (e.g., Spark, AWS)
• Information retrieval, recommender systems, natural language processing, personalization algorithms