Senior Software Engineer, Generative AI, Safety Classifiers, Agentic Systems, Google Ads

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

The Actor Safety Foundational Modeling (ASFM) team's mission is to protect Google Ads users from harm by building the core models and infrastructure that enable the detection and prevention of abusive behavior. We are a medium sized team and the last couple of years have been about building large scale foundational, high-precision ML models and infrastructure that identify and neutralize abusive behavior.

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 $174,000-$252,000 + 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 AI/ML models, including leveraging Large Language Models (LLMs) and Agent infrastructures to understand the behavior of advertisers in the Google Ads ecosystem.
• Build and deploy AI Agents capable of performing complex reasoning, automated investigations, and proactive threat hunting to augment our safety operations.
• Create robust, scalable infrastructure that allows our detection and enforcement teams to identify and act on bad actors quickly and effectively.
• Innovate and rapidly deploy new solutions to ensure we are always one step ahead of those who seek to abuse our platform, leveraging generative AI to simulate and defend against emerging adversarial tactics.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
  
• 2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
• 1 year of experience building and deploying AI Agents.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• 5 years of experience with data structures and algorithms.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
  
• 1 year of experience in a technical leadership role.
• Experience with graph algorithms, machine learning infrastructure, machine learning optimization, Agent Assist, Generative AI.
• Experience developing accessible technologies.