Android Software Engineering Tech Lead Manager, AI/ML

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management or team leadership role.
• Experience with AI Platform and Machine Learning Infrastructure establishing standards and metrics.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• Experience in one or more of the following areas: on-device machine learning, mobile algorithms, LLM/GenAI evaluations, data collection for ML, and Android development.
• Experience successfully launching one or multiple AI/ML-powered user-facing products.
• Experience and domain expertise in AI toolchain, evaluation metrics design, and data management techniques.
• Experience leading and managing distributed teams across the US and Asia.

About the job

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 AI Platform Empowering X (APEX) team's mission is to accelerate and ensure the quality of the AI development lifecycle for Android and Pixel. We are looking for outstanding software engineers to build the stack for scaling the organization's ML needs, which include data strategies, model training, and evaluation techniques, incorporating human feedback for ML quality, on-device optimization, feature development, and quality experiments.

The Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google’s artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world.

The US base salary range for this full-time position is $197,000-$291,000 + 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

• Grow the local team expertise and projects, mentoring the team and removing bottlenecks. Improve the team's design, code, and engineering practices.
• Interface with cross-functional and remote teams, engineering managers, and stakeholders to to influence cross-team priority and roadmap.
• Design tools/platforms/frameworks to enhance intelligent applications development, with a focus on model evaluation, i18n, quality, and performance on Pixel and Android in a private and safe manner.
• Collaborate closely with AI feature teams, model developers and researchers to understand evaluation requirements, provide support, and integrate new models and use cases into the evaluation framework.
• Identify opportunities, develop strategies, and lead roadmaps to improve the reliability, scalability, and efficiency of model evaluation processes.