Senior Staff Software Engineer, Ads Content Safety AI/ML

In most instances, this position requires in-person interviews as part of the hiring process.

Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 7 years of experience leading technical project strategy, ML design and optimizing end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 5 years of experience with design and architecture; and testing/launching software products.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 8 years of experience with data structures and algorithms.
• 5 years of experience in a technical leadership role leading project teams and setting technical direction.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.

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 Ads Content Safety team are seeking an exceptional Senior Staff Software Engineer whose defining characteristic is a relentless, adaptable problem-solving mentality. In this role, you will operate as a technical leader on Ad Safety, serving as the frontline operational and technical anchor for our most critical challenges. Whether the bottleneck is a complex machine learning limitation, a system-level infrastructure failure, or a deep architectural flaw, you possess the attitude and agility to drop into the context, untangle the ambiguity, and drive the solution.

Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business. Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google.

• Design, develop, test, deploy, maintain, and enhance large scale software solutions.
• Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.
• Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.
• Drive technical project strategy, lead large-scale ML infrastructure optimization, and oversee the design and implementation of solutions across multiple specialized ML areas.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Los Angeles, CA, USA; Mountain View, CA, USA.