Software Engineering Manager, Machine Learning, Kids and Families

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.

The Kids and Families team is working to bring new, exciting services and experiences to minors and their families. We are focused on the well-being of kids and families while ensuring that Google is compliant with regulations set by regulatory bodies across the globe.

We are working on many exciting initiatives to grow the user base of minor accounts and families within Google. We are also working on new features, making our services more accessible to other services, and enabling other platforms such as Youtube, Gemini and others to provide better experiences for children and their families.

The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

• Work with Technical Leads to establish and drive a technical road map for your team, mapping business objectives to a cohesive team strategy. Lead the execution and deployment of sophisticated ML models.
• Foster a healthy, high-performing team culture. Manage career growth, performance, and mentorship for engineers on your team.
• Collaborate cross-functionally with peer teams across Search, YouTube, and Core. Partner with Data Science, Product, and Policy to define model behaviors that respect complex regulatory and privacy constraints.
• Guide the team in designing and building scalable data pipelines and training infrastructure for large-scale datasets. Ensure long-term system reliability and robustness by integrating modern ML infrastructure and engineering best practices.
• Align team priorities with broader organization goals and company-wide objectives. Identify and mitigate project risks, manage dependencies, and reduce operational toil across functional lines.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development and system design.
• 3 years of experience in a people management role.
• Experience in one or more disciplines: machine learning, recommendation systems, natural language processing, computer vision, pattern recognition, or artificial intelligence.
• Experience with Large Language Models, NLP, or Generative AI.

Preferred qualifications:

• Experience managing engineering teams, including experience leading managers or tech leads with a commitment to people management responsibilities.
• Experience working on Trust and Safety, user classification, fraud/risk detection, identity verification, or adversarial machine learning.
• Experience with building classifiers, machine learning, AI, ranking, research background.
• Experience working with Data Scientists to improve model quality, develop calibration models, evaluation methods and de-biasing techniques.
• Experience mentoring junior engineers.