AmazonPosted 1d ago

Applied Scientist, Catalog System Services Science

Applied Scientist, Catalog System Services Science at Amazon scores 90 out of 100 on AI centrality, which makes it a Level 4 role on this board.

US, WA, Seattleseniorfull-time$143k-$193k

AI in this role

Pioneer advanced GenAI and multimodal solutions to power next-generation agentic shopping experiences and catalog understanding.

python

ai-researchgenerative-aimachine-learningcomputer-visioninformation-retrievalalgorithm-design

At Amazon Selection and Catalog Systems (ASCS), our mission is to power the online buying experience for customers worldwide so they can find, discover, and buy any product they want. We innovate on behalf of our customers to ensure uniqueness and consistency of product identity and to infer relationships between products in Amazon Catalog to drive the selection gateway for the search and browse experiences on the website. We're solving a fundamental AI challenge: establishing product relevant information at unprecedented scale with Frontier Models and Agents. The scale is staggering: billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity ranging from electronics to groceries to digital content.

The research challenges are immense. GenAI and VLMs hold transformative promise for catalog understanding, but we operate where traditional methods fail: ambiguous problem spaces, incomplete and noisy data, inherent uncertainty, reasoning across both images and textual data, and explaining decisions at scale. Enriching product information requires sophisticated models that reason across text, images, and structured data, all while maintaining accuracy and trust for high-stakes business decisions affecting millions of customers daily.

Amazon's Catalog System Services Science team is looking for an innovative and customer-focused applied scientist to help us make the world's best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services. You will pioneer advanced GenAI solutions that power next-generation agentic shopping experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your algorithmic ideas at scale, across millions of customers.

Key job responsibilities
- Formulate novel research problems at the intersection of GenAI, multimodal learning, and large-scale information retrieval. In essence, translating ambiguous business challenges into tractable scientific frameworks
- Design and implement leading models leveraging frontier models, and agentic architectures to enrich catalog information at billion-product scale
- Pioneer explainable AI methodologies that balance model performance with scalability requirements for production systems impacting millions of daily customer decisions
- Own end-to-end ML pipelines from research ideation to production deployment, processing petabytes of multimodal data with rigorous evaluation frameworks
- Represent the team in the broader science community - publishing findings, delivering tech talks, and staying at the forefront of GenAI, VLM, and agentic system research

Basic qualifications

- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- 2+ years of building machine learning models or developing algorithms for business application experience
- Prior experience in the domains of LLMs, or large-scale deep learning systems

Preferred qualifications

- Publications in top-tier venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, EMNLP, ACL, NAACL, COLING, KDD, SIGMOD, WWW, AAAI, or similar
- Experience with multimodal LLMs, including hands-on post training techniques

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 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.

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 https://amazon.jobs/en/benefits.

USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually

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Skills and AI tools this role asks for

AI ResearchGenerative AIMachine LearningComputer VisionInformation RetrievalAlgorithm DesignPython

Questions you could be asked

Tell me about a research question you investigated. What did you find?
Tell me about a project where generative ai was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?
Walk me through a computer vision problem you solved, from raw data to a deployed model.
Tell me about a project where information retrieval was part of your work. What did you do?

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List these exact terms on your resume: AI Research, Generative AI, Machine Learning, Computer Vision, and Information Retrieval. An applicant tracking system matches the wording, not the idea.
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Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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