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Associate Principal Strategist, Trust and Safety, Product Fairness

Google · United States · On-site

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About Google

Learn more about Google. Explore our innovative AI products and services, and how we. Backed by Kleiner Perkins.

About the role

Trust & Safety team members are tasked with identifying and taking on the biggest problems that challenge the safety and integrity of our products. They use technical know-how, excellent problem-solving skills, user insights, and proactive communication to protect users and our partners from abuse across Google products like Search, Maps, Gmail, and Google Ads. On this team, you're a big-picture thinker and strategic team-player with a passion for doing what’s right.

What they're looking for

  • Bachelor's degree or equivalent practical experience
  • 7 years of experience in data analytics, Trust and Safety, policy, cybersecurity, or related fields
More about this role
  • Develop clear guidelines for identifying and assessing potential fairness implications across emerging generative AI technologies at scale.
  • Design and build scaled fairness evaluations and provide subject expertise on ‘red teaming’ sessions.
  • Perform in-depth analysis into fairness issues and vulnerabilities. Prepare written reports outlining user impact issues, abuse vectors, and trends, and effectively communicate findings to product and company leadership.
  • Provide guidance to product teams in identifying and mitigating fairness challenges by providing technical, qualitative, and quantitative data support in assessing ML models and products.
  • Respond to time sensitive requests, and provide expert guidance to executives and cross-functional working groups to define strategies and timely solutions for supporting responsible product development.
  • Bachelor's degree or equivalent practical experience.
  • 7 years of experience in data analytics, Trust and Safety, policy, cybersecurity, or related fields.
  • Master's degree or PhD in a relevant field.
  • Education in, or experience with, machine learning.
  • Experience in SQL, building dashboards, data collection/transformation,...

Read the full posting on Google's site ↗

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