Note: The job is a remote job and is open to candidates in USA. Amazon Science is seeking an Applied Scientist to help build next-generation customer memory and personalization systems. The role involves designing and building machine learning and large language model-powered solutions to enhance customer experiences by understanding and remembering customer behavior over time.

Responsibilities

• Design and build ML and LLM-powered solutions for Amazon's customer memory and personalization systems
• Own the end-to-end delivery of ML solutions, from problem formulation and modeling to offline and online experimentation, and production deployment at scale
• Deliver high-quality, scalable systems that power customer-facing experiences
• 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
• Collaborate closely with engineering and product teams to translate research into measurable customer impact

Skills

• Knowledge of programming languages such as C/C++, Python, Java or Perl
• Experience in patents or publications at top-tier peer-reviewed conferences or journals
• PhD, or a Master's degree and experience in CS, CE, ML or related field research
• Strong communication and collaboration skills
• 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

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