Applied Science II, Product Knowledge GenAI

The Catalog Services Product Knowledge team is seeking an Applied Scientist for the Catalog Services organization. Our vision is simple: build AI systems that are capable of a deep product understanding so we can organize and scale the catalog metadata (schema) for Amazon e-commerce catalog worldwide. This is a complex problem because the magnitude of products entities (attributes values constraints) to be modeled to cover all the Amazon products worldwide. You will work on initiatives (models artifacts) aim to solve the problem of producing Catalog schema with less reliance on humans and deliver them into the Amazon production ecosystem. Your efforts will build a robust ensemble of ML and GenAI techniques that will scale our catalog artifacts with a high precision across countries and languages.

The scientist will own investments in machine learning natural language processing GenAI to solve real world problems at scale. The teams output affects the velocity at which we build product schema and support the largest e-commerce catalog and impact million of customers. The team builds solutions ranging from automatic generation of product metadata classification of entities validation of concepts against customer traffic creation of agents solving complex tasks mimicking human decisions at high precision etc; all these developments drive true understanding of products at scale.

The ideal candidate has deep expertise in one or several of the following fields: Generative AI Agents LLMs Web search Applied/Theoretical Machine Learning Deep Neural Networks Classification Systems Clustering Natural Language Processing. S/he has a strong publication record at relevant academic venues and proven experience in launching products/features in the industry.


Key job responsibilities
- Formulate open research problems at the intersection of GenAI multimodal reasoning and large-scale information retrievaldefining the scientific questions that transform ambiguous real-world catalog challenges into models applied to production with high-impact
- Push the boundaries of models and agentic architectures by designing novel approaches to catalog understanding schema inference where the problem complexity (billions of products) demands methods that dont yet exist
- Make frontier models reliableadvancing uncertainty calibration confidence estimation and interpretability methods so that frontier-scale GenAI systems can be trusted for autonomous catalog decisions
- Own the full research lifecycle from problem formulation through production deployment designing rigorous experiments iterating on ideas rapidly and seeing your research directly improve data and catalog operations
- Shape the teams research vision by defining technical roadmaps that balance foundational scientific inquiry with measurable product impact
- Represent the team in the broader science community publishing findings delivering tech talks and staying at the forefront of GenAI and agentic system research


About the team
The teams mission is to infer knowledge understand and derive product schema for all Amazon products entering the Catalog. The work is critical to power drive policies on how products will be merchandised guide Selling Partners inform models how to infer attributes. All this information drives the navigational Taxonomy Search and Detail Page experiences impacting million of customers. The scientist collaborates closely with teams across the organization and outside the Catalog (Search Personalization etc) that rely on this teams developments.

- PhD or Masters degree and 4 years of CS CE ML or related field experience
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing
- 2 years of building machine learning models or developing algorithms for business application experience

- 4 years of deep learning computer vision human robotic interaction algorithms implementation experience
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Experience in solving business problems through machine learning data mining and statistical algorithms
- Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
- Experience with LLMs VLMs foundation models or large-scale deep learning systems including multimodal pretraining fine-tuning RLHF prompt engineering or agentic architectures
- Publications in top-tier venues such as NeurIPS ICML ICLR CVPR ICCV EMNLP ACL NAACL COLING KDD SIGMOD WWW AAAI or similar

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at WA Seattle - 142800.00 - 193200.00 USD annually