Engineering Manager, Image Search Ranking

Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

As a part of the team powering Google Images, the world's largest image search engine, you will be responsible for the ranking of image results and work on all aspects of quality including mining and developing new foundational signals, defining evaluation methods for algorithmic changes, and continuously exploring the latest developments in research to apply them to large-scale problems.

In this role, you will help lead technical initiatives across critical new investment areas, including Shopping in Images, Personalization in Image Results and Features, Search Refinements, and the transition toward an AI-Organized Search Results Page.

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.

The US base salary range for this full-time position is $207,000-$300,000 + 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

• Build, mentor, and grow a team of software engineers, guiding their technical direction, career development, and execution.
• Drive the technical strategy for evaluating opportunities to improve the current ranking of image results.
• Oversee the development of ranking improvements, including advances in retrieval, scoring, and diversification of results.
• Guide the team in using a broad spectrum of available technology at Google to solve problems at scale: from Large Language Model (LLMs) like Gemini to ScaM-based retrieval, to more traditional information retrieval techniques.
• Reiterate on evaluation methods used for ranking changes, constantly aligning them with evolving product goals and our 2026 strategic investments.

Minimum qualifications:

• Bachelor’s degree, or equivalent practical experience.
• 8 years of experience in software development and working with algorithms.
• 2 years of experience in a people management or team leadership role.
• Experience coding in C++ or Python.
• Experience with data analysis.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• Experience managing a team of software engineers.
• Experience in Search Quality and ranking systems.
• Experience with applied machine learning and ML training and serving at Google.
• Experience architecting and deploying machine learning solutions within AI/ML.
• Ability to understand product needs, articulate them into tasks for human raters or AI prompts, understand user behavior, analyze data, and interpret model outputs.