[Remote] Applied Scientist, Personalization, Personalization
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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