Applied Scientist – Customer Personalization

About the role

We are looking for an Applied Scientist to help build Amazon’s next‑generation customer memory and personalization systems. You will design and implement machine‑learning and large‑language‑model solutions that transform noisy, unstructured signals into high‑quality representations of customer preferences, intents, and life events, powering real‑time personalized experiences.

Key responsibilities

• Design, develop, and deploy ML and LLM‑powered solutions for Amazon’s customer memory layer.
• Own end‑to‑end delivery from problem formulation, modeling, offline/online experimentation to production deployment at scale.
• Drive work across fact extraction, memory quality, temporal reasoning, and grounded personalization while balancing precision, recall, latency, and coverage.
• Collaborate closely with engineering and product teams to translate research into measurable customer impact.

Required profile

• PhD or Master’s degree with research experience in computer science, machine learning, or related fields.
• Strong record of patents or publications at top‑tier peer‑reviewed conferences or journals.
• Excellent communication and collaboration skills.

Required skills

• Proficiency in programming languages such as C/C++, Python, Java, or Perl.
• Experience building and launching deep learning and machine learning models for business applications.
• Solid knowledge of big‑data and cloud technologies (e.g., Spark, AWS).
• Experience with information retrieval, recommender systems, natural language processing, and personalization algorithms.