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.
In this role, you will play a vital role in ensuring that Google Cloud’s Artificial Intelligence (AI) products are not only powerful but also safe, secure, and trustworthy. Your investigative skills, understanding of potential security harms, for user protection will help the teams solve testing problems in AI security and abuse at scale. You will proactively identify and mitigate emerging threats within the AI landscape, ranging from adversarial attacks to potential misuse of generative technologies. You will synthesize large datasets to uncover patterns of abuse, ensuring that Google's AI deployments remain resilient against sophisticated exploitation while upholding our responsibility for safe AI growth.
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
- Develop and deploy scalable safety solutions for Cloud AI products by leveraging advanced machine learning and AI techniques.
- Use data analysis to discover and interpret how attackers exploit Cloud AI infrastructure or use Application Programming Interfaces (APIs) for abuse, identifying weak points in our systems.
- Define what constitutes abuse in ambiguous or highly novel AI use cases, ensuring our guidelines adapt to AI-driven attacks.
- Analyze and measure generative/agentic AI risks using benchmarking, dataset design, and scaled usage monitoring.
- Drive the rapid response for high-priority AI security incidents, conducting through Root Cause Analyses (RCAs) to implement sustainable long-term solutions. Partner with Engineering and Product teams to identify, prioritize, and develop strategies against the most pressing and novel AI threats.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience in data analysis or data science, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
- Experience with SQL.
Preferred qualifications:
- Master's degree or PhD in a technical discipline (e.g., Computer Science, Statistics, Mathematics, Operations Research, etc.).
- Experience in security threat or abuse detection.
- Experience in one domain, such as anomaly detection, security threats analysis and investigation, time-series analysis, Cloud Application Programming Interfaces (APIs), or metrics and reporting.
- Understanding of generative AI technologies, Large Language Models (LLMs) and AI agents.
- Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.