Content Risk Analyst, Asci, Asci

Amazon Amazon · Big Tech · H, Costa Rica +1 · Project/Program/Product Management--Non-Tech

This role focuses on the operational aspects of AI initiatives within Amazon's Alexa team, specifically involving data annotation, quality assurance for AI models, red teaming, customer feedback analysis, and incident monitoring. The candidate will work with essential back-end operations to maintain the quality and accuracy of AI initiatives, create and manage test datasets, and contribute to process improvements.

What you'd actually do

  1. Lead the creation and annotation of MLOGs for model improvement across multiple domains
  2. Design and execute comprehensive red teaming strategies across multiple Alexa experiences
  3. Lead the analysis of complex customer feedback, including emerging trends and edge cases
  4. Oversee the monitoring process for policy violations and emerging issues
  5. Propose and implement process improvements to enhance operational efficiency

Skills

Required

  • 1+ years of data-driven business operations processes experience
  • Experience with Microsoft Excel
  • Speak, write, and read fluently in English
  • Experience with Microsoft Office products & applications
  • In-depth understanding of AI/ML concepts, including current trends and challenges
  • Strong analytical and problem-solving skills, particularly for complex AI-related issues
  • Excellent communication skills for collaborating with various stakeholders
  • Ability to manage multiple priorities and adapt to rapidly changing requirements in the AI field

Nice to have

  • Speak, write, and read fluently in French
  • Experience in regulatory compliance management with government agencies
  • Bachelor's degree in Law, or 2+ years of Product Safety & Compliance Law experience
  • Mentor and provide guidance to L2 team members

What the JD emphasized

  • AI/ML concepts
  • complex AI-related issues
  • AI field

Other signals

  • MLOps
  • data annotation
  • red teaming
  • customer feedback analysis
  • incident monitoring