About the job

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.

As a Security and Applied AI Analyst for the Chrome Web Store and Extensions Security team, you will leverage your domain expertise to perform technical investigations, uncover abuse vectors and techniques, and use your combined problem-solving and strategic acumen to improve our protection protocols and evolve them into scalable, AI driven systems. You will collaborate closely with engineering and product partners to identify threats, mitigate risks, and launch new protection mechanisms to help make the Chrome platform ecosystem the safest in the world. You will deploy solutions, both algorithmic and operational which will enable Google to identify and flag abuse more easily, more effectively, and at scale.

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 $132,000-$189,000 + 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

• Conduct investigations to catch harmful and abusive behavior and actors, enforce our product policies, learn abuse patterns, and establish ground truth data to train automated systems.

• Reverse engineer potentially harmful extensions (written in Javascript) to understand their operations and impact on the Chrome ecosystem.

• Design AI-powered and automated solutions that enable scalable identification of malware, spam, and other harmful extensions.

• Collaborate with other teams to develop and deploy new detection methods and signals, train and mentor a large team of security reviewers.

• Enhance operational workflows via AI integration, process improvements, and identifying automation opportunities.

Minimum qualifications

• Bachelor's degree or equivalent practical experience.

• 2 years of experience in building or reverse engineering JavaScript, PHP, mobile/web applications.

• Experience with quantitative and qualitative analysis, using languages like SQL and Python.

Preferred qualifications

• Master's degree in Computer Science, Information Technology, quantitative or quantitative discipline (e.g., Computer Science, Statistics, Mathematics, Operations Research, etc.).

• Experience in cybersecurity principles and practices.

• Experience with static and dynamic analysis of malicious binaries.

• Knowledge of one or more of the following areas: statistical analysis and machine learning libraries (e.g., R, Tensorflow), programming languages (e.g., Python), Large Language Models (LLMs) or applied AI.

• Familiarity with the development lifecycle and security considerations specific to browser extensions or similar technologies.

• Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.