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. You work globally and cross-functionally with Google engineers and product managers to identify and fight abuse and fraud cases at Google speed - with urgency. And you take pride in knowing that every day you are working hard to promote trust in Google and ensuring the highest levels of user safety.
Google is committed to building products that are both innovative and safe for our users. Our Trust and Safety Responsible AI Testing team is at the heart of this effort, protecting the integrity of our platforms by delivering actionable and objective content abuse insights.
Within the RAI Testing SCALE team, we're driving a transformation in how we approach AI testing by shifting toward a highly scalable, automated model. We partner closely with subject matter experts across Trust & Safety, product, and engineering to operationalize their domain expertise into robust testing frameworks. By building self-service infrastructure that empowers product teams to autonomously meet standard safety bars, we are able to focus our specialized expertise on executing high-risk, bespoke evaluations and pioneering tests for novel AI paradigms. Together, we integrate AI and automation to turn safety insights into action.At Google we work hard to earn our users’ trust every day. Trust & Safety is Google’s team of abuse fighting and user trust experts working daily to make the internet a safer place. We partner with teams across Google to deliver bold solutions in abuse areas such as malware, spam and account hijacking. A team of Analysts, Policy Specialists, Engineers, and Program Managers, we work to reduce risk and fight abuse across all of Google’s products, protecting our users, advertisers, and publishers across the globe in over 40 languages.
The US base salary range for this full-time position is $159,000-$231,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Leverage SQL and Python to embed self-service frameworks and automated evaluation systems into developer pipelines, enabling product teams to run standard evaluations autonomously.
- Act as the operational executor for complex, high-risk, and bespoke strategic evaluations, bridging the gap between defining safety quality and enforcing it.
- Partner with cross-functional stakeholders—including engineering teams, policy experts, and launch leadership—to develop and own intake triage and handoff governance protocols.
- Develop, maintain, and execute automated quality rubrics across testing services to ensure actionable results. Drive initiatives to significantly increase the use of automated evaluations and optimize operational resource allocation.
- Work autonomously to identify and solve problems and collaborate effectively within a team to develop comprehensive solutions. This role works with sensitive content or situations and may be exposed to graphic, controversial, and/or upsetting topics or content.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
- 5 years of experience managing projects and defining project scope, goals, and deliverables.
Preferred qualifications:
- Master's degree in a quantitative discipline.
- 5 years of experience with one or more of the following languages: SQL, R, Python, or C++.
- 5 years of experience with machine learning systems.
- Excellent written and verbal communication skills.