Applied Scientist: GenAI for Large-Scale Catalog

Amazon; Sunnyvale (CA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

RSUs

Job summary

Amazon Selection and Catalog Systems (ASCS) is seeking an innovative applied scientist to advance product-to-product relationship inference at scale. You will collaborate with tech and business leaders to build state-of-the-art algorithms, models, and services for the world’s largest product catalog.

The role focuses on GenAI solutions and multimodal reasoning across images and text to improve catalog quality for hundreds of millions of customers.

Qualifications

• PhD or MS with 4+ years in CS/CE/ML or related field.
• Experience programming in Java, C++, Python.
• 2+ years building ML models or algorithms for business applications.

Responsibilities

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

Skills

Java

C++

Python

ML model development

Education

PhD or MS in CS/CE/ML or related

Tools

Java

C++

Python

Job description

Amazon Selection and Catalog Systems (ASCS) is seeking an innovative applied scientist to advance product-to-product relationship inference at scale. You will collaborate with tech and business leaders to build state-of-the-art algorithms, models, and services for the world’s largest product catalog.

The role focuses on GenAI solutions and multimodal reasoning across images and text to improve catalog quality for hundreds of millions of customers.