Senior Staff Software Engineer, Infrastructure, Google Ads

Senior Staff Software Engineer, Infrastructure, 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. With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

We are seeking an exceptional Senior Staff Engineer to serve as the Technical Lead (TL) for our entire Ads Safety Classification organization. This is a role responsible for defining and driving the technical goal across our Machine Learning (ML) and non-ML infrastructure, classification platform, and analyst tools. You will lead the charge in building the next generation of our ad safety systems, including the foundational infrastructure for integrating LLMs and Agents at a massive scale.

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 $248,000-$349,000 + 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.

Minimum Qualifications:

• Bachelor's degree in Computer Science or related technical field, or equivalent practical experience.
• 8 years of experience in software development.
• 7 years of experience building and developing large-scale infrastructure, distributed systems or networks; or experience with compute technologies, storage, or hardware architecture.
• 5 years of experience with design and architecture and testing/launching software products.

Preferred Qualifications:

• Experience in machine learning infrastructure, model serving, and data pipelines at a massive scale.
• Experience in building and maintaining internal tooling that supports human-in-the-loop workflows.
• Understanding of the tests for protecting users online and a passion for the Ads Safety mission.
• Ability to track record of shipping major platform and infrastructure initiatives that have a significant and measurable impact on the business.

Responsibilities:

• Define and own the long-term technical strategy for the entire Ads Safety Classification organization. Be responsible for the health, scalability, and security of all systems from the platform to the analyst tools.
• Lead through influence by driving alignment and a unified technical roadmap across multiple engineering teams to solve the most ambiguous tests.
• Design and oversee the architecture of our large-scale classification systems, including ensuring a cohesive, goal for how Machine Learning (ML) models, non-ML classifiers, and human expertise interact within the platform.
• Act as an expert for critical technical issues, and be the go-to person for unblocking projects and ensuring architectural integrity.
• Mentor and grow the technical talent within the organization, including other executive engineers, and set goals for engineering excellence and foster a culture of technical.