As an Applied Scientist, you will design and build ML and LLM-powered solutions for Amazon's customer memory and personalization systems. You will work on how customer knowledge is extracted, validated, and applied in production systems.
You will own the end-to-end delivery of ML solutions, from problem formulation and modeling to offline and online experimentation, and production deployment at scale. You will deliver high-quality, scalable systems that power customer-facing experiences.
You will 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.
You will collaborate closely with engineering and product teams to translate research into measurable customer impact.
Basic Qualifications
– 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.
Preferred Qualifications
– 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.
