Principal Developer, Ads Safety Machine Learning
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Minimum qualifications:
- Bachelor’s degree in Computer Science or equivalent practical experience.
- 15 years of experience in software engineering.
- Experience with technical innovation and leadership in cross-functional engineering environments.
- Experience in machine learning, AI, and their applications in threat detection, fraud prevention, or content compliance.
- Experience in managing multiple initiatives, including coordination across geographically dispersed, cross-functional teams.
Preferred qualifications:
- Master’s degree or PhD in Computer Science or related technical fields.
- Experience in Cybersecurity or Ads Safety Domain.
- Ability to balance detailed, technical guidance with “big picture” strategy and enabling teams to deliver products that are effective.
- Exceptional communication and collaboration skills, with the ability to influence technical and non-technical stakeholders effectively.
- Has a demonstrated passion for, and has provided thought leadership around, user privacy, security and ethics.
- Demonstrated proficiency in adversarial thinking, threat analysis, and policy enforcement in fast-paced or high-stakes environments.
About the job
The Ads Safety team is responsible for building systems that ensure safety, fairness, and trustworthiness. We review every ad, advertiser, publisher, and merchant in our ecosystem to ensure that they comply with ads policies and publisher controls. At Google’s scale, Ads Safety requires advanced machine learning and artificial intelligence, in-depth threat analysis, and a relentless focus on adapting to emerging risks. As a Principal Developer on the Ads Safety team you will be responsible for designing and advancing the technical road map for detecting malicious activity and evaluating ad content at massive volumes. This includes integrating robust ML models with verification and review frameworks, as well as partnering across policy, legal, and compliance teams to maintain alignment with regulatory standards and the highest levels of user trust. You will drive the technical vision and execution of machine learning solutions aimed at both Actor Safety and Content Safety. The actor dimension focuses on distinguishing legitimate users from malicious entities who may engage in fraud, scams, or counterfeit activities. The content dimension deals with ensuring that ad content complies with our policies, addresses user concerns, and avoids harmful or misleading information to our users.
Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
The US base salary range for this full-time position is $278,000-$399,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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
- Architect and implement ML/AI models to detect malicious behavior (actor focused) and non-compliant or harmful ad content (content focused) at scale.
- Work across a large and diverse organization that will provide an opportunity to partner closely with leads across the Ads ecosystem to build and drive technical and product consensus.
- Guide and inspire engineers to take in complex challenges in both actor and content safety. Provide strategic direction on architecture, design, and best practices.
- Define key performance indicators to track the effectiveness of our machine learning/AI platforms.
- Define and evolve the technical machine learning/AI road map for Ads Safety, ensuring it aligns with Google’s mission to provide a secure and trustworthy platform, and helps us to meet our magnitude improvement goals.
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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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