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.
The Workspace AI Trust and Safety team enables the rapid growth of Workspace AI businesses by curbing associated safety and security risks. We support products throughout their life cycle by advancing safety protection mechanisms in the earliest stages of design. Our portfolio includes both pre- and post-launch capabilities, ensuring cutting-edge AI products are powerful, safe, secure, and aligned with our AI Principles.
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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $159000 - $231000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Contribute to project scoping, manage project priorities and technical resource allocation, and co-develop engineering priorities and solutions for Workspace AI product safety and prompt injection evaluations within your projects.
- Design and implement anti-abuse policies, strategies, and workflows. Build processes and tests to anticipate and address future AI safety issues.
- Solve complex AI abuse and safety problems using a multi-faceted approach, identifying new safety and quality issues quickly through data analysis.
- Propose and implement safety program changes by collaborating with engineers and product managers, guiding adjacent project timelines and goals.
- Construct accurate and efficient queries of high complexity independently to extract and manipulate large volumes of critical product data. Compute statistics (e.g., precision, recall, and balanced accuracy) to analyze and evaluate classifier performance, identifying nuanced or easily missed problems in complex technical models.
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.
- Experience in one or more programming languages (e.g., Python, SQL, Go, C++, Java), or with machine learning, anomaly detection, or AI models.
Preferred qualifications:
- Master's degree or PhD in a quantitative discipline.
- Experience building and deploying anti-abuse systems, workflows, or processes at scale.
- Expertise in exploratory data analysis and statistical analysis with a track record of identifying non-obvious patterns in large datasets.
- Proficient in code comprehension (extracting relevant information from reading code in core languages) and engineering project management.
- Demonstrated ability to navigate ambiguity and solve complex, multi-faceted quality and safety problems in the AI safety domain.
- Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.