Applied Scientist: Generative AI & LLMs for Smart Shopping

Amazon Inc.

Seattle (WA)

On-site

USD 136,000 - 184,000

Full time

3 days ago
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Benefits offered by this job

RSUs
Health insurance
401(k) matching
Paid time off

Job summary

Amazon.com Services LLC is seeking an Applied Scientist to advance AI-driven customer experiences for BuyForMe and similar products. You will shape LLM-powered solutions, agentic systems, and robust evaluation frameworks that improve pre-purchase, purchase, and post-purchase workflows.

You will collaborate with engineers, product managers, and researchers to turn business challenges into scalable scientific solutions, run experiments on real data, and contribute to publications, patents, and

Qualifications

  • Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field.
  • Experience programming in Java, C++, Python or related language.
  • Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse.

Responsibilities

  • Invent, implement, and evaluate state-of-the-art models and agentic systems that directly impact customer experience.
  • Conduct research that may lead to publications, patents, or cross-Amazon technical influence.
  • Collaborate with engineers, product managers, and other scientists to translate business challenges into scalable science solutions.
  • Run experiments with real customer data and validate hypotheses in a high-impact product environment.
  • Drive excellence in model performance, safety, reliability, and evaluation frameworks.

Skills

Java
C++
Python
SQL

Education

Master's degree in computer science / mathematics / statistics / machine learning

Tools

Oracle

Job description

Amazon.com Services LLC is seeking an Applied Scientist to advance AI-driven customer experiences for BuyForMe and similar products. You will shape LLM-powered solutions, agentic systems, and robust evaluation frameworks that improve pre-purchase, purchase, and post-purchase workflows.

You will collaborate with engineers, product managers, and researchers to turn business challenges into scalable scientific solutions, run experiments on real data, and contribute to publications, patents, and

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