Applied Scientist – Customer Memory & Personalization

About the role

We are seeking an Applied Scientist to help build Amazon’s next-generation customer memory and personalization systems. The team creates a customer memory layer that extracts, curates, and reasons over customer knowledge to power highly relevant experiences.

Key responsibilities

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

Required profile

• Knowledge of programming languages such as C/C++, Python, Java or Perl.
• Experience with patents or publications at top‑tier peer‑reviewed conferences or journals.
• PhD or a Master’s degree with research experience in computer science, computer engineering, machine learning or related fields.
• Strong communication and collaboration skills.

Required skills

• Deep learning and machine‑learning model development for business applications.
• Big data and cloud technologies (e.g., Spark, AWS).
• Information retrieval, recommender systems, natural language processing, and personalization algorithms.
• Experience building and launching production‑scale ML solutions.