Senior Staff Software Engineer - AI Mode and AI Overviews Helpfulness

• Own the technical strategy and roadmap for whole-response helpfulness across AI mode and AI overviews.
• Architect scalable quality infrastructure and closed-loop self-improving systems that shorten the path from experiment to launch.
• Drive quality improvements out-of-model and in-model.
• Define how all aspects of our work (measurement, hill-climbing, upstreaming) should be adjusted to account for response aspects beyond text.
• Establish strong collaborations to align priorities and technical direction.

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 working with end-to-end applied machine learning (e.g., model deployment, model evaluation, data processing, debugging).
• 5 years of experience with design and architecture; and testing/launching software products.
• Experience in AI/ML quality evaluation and improvement.
  
• Experience integrating generative AI tools or LLM interfaces into workflows.
  

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.
• Experience driving quality improvements out-of-model (prompting, APO, modular serving, orchestration) and in-model (post-training and evals).
  

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.

This team focuses on improving foundational AI overview quality from collaboration with Deepmind partners to improve underlying one recipe models to end-to-end quality with prompt optimization, quality evaluations, and live experiments. Our team's mission is to deliver quality by optimizing response helpfulness to ensure the right content is included in a way that is easy to consume.

In this role, you will work on improving Google Search's flagship GenAI experiences, including AI overviews and AI mode, to be a trusted knowledge companion with conversations that feel natural and effortless.

In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

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.

• 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 working with end-to-end applied machine learning (e.g., model deployment, model evaluation, data processing, debugging).
• 5 years of experience with design and architecture; and testing/launching software products.
• Experience in AI/ML quality evaluation and improvement.
  
• Experience integrating generative AI tools or LLM interfaces into workflows.