GenAI & Multimodal Catalog Scientist

Amazon; Seattle (WA); On-site; USD 142,800 - 193,200; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon is seeking an innovative Applied Scientist to advance GenAI and multimodal reasoning for the Amazon Selection and Catalog Systems. You will partner with leaders to build state-of-the-art algorithms and services inferring product-to-product relationships across billions of catalog entries.

You will prototype, deploy, and scale AI solutions, solving high-stakes challenges with massive datasets and a global impact on shopping experiences for hundreds of millions of customers.

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.

Responsibilities

• Formulate open research problems at the intersection of GenAI, multimodal reasoning, and large-scale information retrieval.
• Push the boundaries of VLMs and foundation models to infer product identity and catalog understanding.
• Advance model deployment by developing distillation, compression, and efficient inference techniques at scale.
• Make frontier models reliable through uncertainty calibration and interpretability methods.
• Own the full research lifecycle from problem formulation to production deployment.
• Shape the team’s research vision by defining technical roadmaps balancing science with product impact.
• Mentor scientists and engineers on advanced ML techniques and experimental design.
• Represent the team in the broader science community through publications and talks.

Skills

Java

C++

Python

Machine Learning

Education

PhD, or Master’s degree in CS/CE/ML or related field

Master’s degree

Job description

Amazon is seeking an innovative Applied Scientist to advance GenAI and multimodal reasoning for the Amazon Selection and Catalog Systems. You will partner with leaders to build state-of-the-art algorithms and services inferring product-to-product relationships across billions of catalog entries.

You will prototype, deploy, and scale AI solutions, solving high-stakes challenges with massive datasets and a global impact on shopping experiences for hundreds of millions of customers.