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Applied Scientist, RISC

1 month ago

Arlington, Virginia, United States Amazon Full time

About Amazon Regulatory Intelligence, Safety, and Compliance (RISC). Our vision is to make Amazon the most trusted shopping destination for safe and compliant products. We take a science-first approach to building technology, products, and services that protect customers from unsafe, illegal, controversial, or policy-violating products.

Job Summary

We are seeking an exceptional Applied Scientist to join our team of experts in machine learning and AI. You will work on challenging problems across diverse compliance domains, leveraging and training state-of-the-art multi-modal and large-language-models (LLMs) to detect illegal and unsafe products across the Amazon catalog.

Key Responsibilities

  • Design and evaluate state-of-the-art algorithms and approaches in multi-modal classification, large language models (LLMs), intent detection, information retrieval, anomaly and fraud detection, and generative AI.
  • Translate product and CX requirements into measurable science problems and metrics.
  • Collaborate with product and tech partners and customers to validate hypothesis, drive adoption, and increase business impact.
  • Conduct research in a corporate setting and publish high-quality scientific papers in internal and external peer-reviewed conferences.

A Day in the Life

You will work on hard science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. You will work in a highly collaborative environment where you can analyze and process large amounts of image, text, and tabular data.

About the Team

We are a team of scientists and engineers building AI/ML solutions to make Amazon the most trusted shopping destination for safe and compliant products. We work on machine learning problems for multi-modal classification, intent detection, information retrieval, anomaly and fraud detection, and generative AI.

Basic Qualifications

  • PhD or Master's degree and 5+ years of applied research experience.
  • Experience programming in Java, C++, Python, or related languages.
  • Experience with neural deep learning methods and machine learning.
  • Experience conducting research in a corporate setting.

Preferred Qualifications

  • Experience with large-scale machine learning systems, including profiling and debugging, and understanding of system performance and scalability.