Applied Scientist
Amazon
Applied Scientist
Amazon
Sells products online and rents cloud computing
We are seeking an Applied Scientist to help build Amazon’s next-generation customer memory and personalization systems.
Are you interested in building systems that move beyond reacting to customer behavior, to actually understanding and remembering it over time? Our team is building Amazon’s customer memory layer – a system that extracts, curates, and reasons over customer knowledge to power next-generation personalization. This includes transforming noisy, unstructured signals into durable, high-quality representations of customer preferences, intents, and life events, and using them in real time to improve customer experiences.
We are part of Amazon’s Personalization organization, a high-performing group that leverages large-scale machine learning, generative AI, and distributed systems to deliver highly relevant customer experiences.
We tackle challenging problems at the intersection of information extraction, knowledge representation, LLM reasoning, and recommendation systems. Our systems operate under real-world constraints of scale, latency, and quality, requiring careful tradeoffs between precision, recall, and responsiveness. This team plays a central role in defining how Amazon understands its customers, and how that understanding is applied across the shopping experience.
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.
Please visit https://www.amazon.science for more information.
- 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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Amazon runs the largest online store in the United States and rents cloud computing to businesses and governments through Amazon Web Services. AWS pioneered renting computing power over the internet, and Amazon built its own delivery network to get orders to customers quickly. Shoppers buy from Amazon and from independent sellers on its store, and Prime members pay a subscription for fast free shipping, streaming video and music, and other perks. AWS rents out computing power, storage, databases, and AI tools so companies can run software without owning servers, and Amazon also makes Kindle e-readers and Echo speakers with the Alexa assistant. Jeff Bezos founded Amazon in 1994, and it is based in Seattle, Washington.
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