Amazon.com Services LLC
Technology
AppliedScientist
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Applied Scientist at Amazon.com Services LLC. Skills: Generative AI, VLMs, Multimodal learning, Agentic architectures. Formulate novel research problems. Translate business challenges into scientific frameworks”
Industry & Context.
Solving fundamental AI challenge; Ambiguous problem spaces; Incomplete and noisy data; Inherent uncertainty; Reasoning across images and text; Explaining decisions at scale
What They're Looking For.
Must Have
Master's degree and 4+ years experience, 2+ years ML model building experience, Programming in Java, C++, Python
Nice to Have
PhD preferred, LLMs experience, Foundation models experience, Large-scale deep learning experience, Visual Language Models experience, Multimodal transformers experience, Vision-language pretraining experience, Explainable AI experience, Model interpretability experience, Uncertainty quantification experience, Generative AI hands-on experience, Prompt engineering experience, Fine-tuning experience, RLHF experience, Agentic architectures experience, Deploy ML models at scale experience, Processing billions of data points experience
What You'll Do.
Formulate novel research problems
Translate business challenges into scientific frameworks
Design and implement models
Leverage foundation models
Leverage agentic architectures
Solve product identity problems
Solve relationship inference problems
Solve catalog understanding problems
Pioneer explainable AI methodologies
Balance model performance with scalability
Process multimodal data
Define research roadmaps
Mentor peer scientists
Represent team in science community
How You'll Work.
Team & Collaboration
Collaborative environment
Communication Scope
Data presentation
Full Job Description
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 identity and relationships at unprecedented scale. Using Generative AI, Visual Language Models (VLMs), and multimodal reasoning, we determine what makes each product unique and how products relate to one another across Amazon's catalog. The scale is staggering: billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity—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. Establishing product identities and groupings requires sophisticated models that reason across text, images, and structured data—while maintaining accuracy and trust for high-stakes business decisions affecting millions of customers daily. Amazon's Item and Relationship Platform group 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 to infer product-to-product relationships that matter to our customers. You will pioneer advanced GenAI solutions that power next-generation agentic shopping experiences, working in a collaborative environment where
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