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Job Details
Posted date: Aug 22, 2025
Location: Seattle, WA
Level: Director
Estimated salary: $298,500
Range: $248,000 - $349,000
Description
Lead the technical direction for GKE AI/ML workload efficiency and optimization, setting the direction and leading a team of engineers. Lead a culture of high performance, innovation, and psychological safety, making your team the premier destination for top engineering talent. Create clarity and focus in a fast-paced, ambiguous environment, transforming high-level goals into a clear, actionable agenda for the team. Drive cross-functional collaboration to identify and resolve critical gaps across the GKE and GCE stacks, building a seamless platform for AI workloadsIn this role, you will lead a team of software engineers and drive the evolution of the Google Kubernetes Engine (GKE) AI ecosystem.
You will make GKE the ultimate platform for AI and machine learning workloads. You and your team will be at the heart of this transformation, building the tools and infrastructure that enable developers and companies to innovate faster and more efficiently.
The US base salary range for this full-time position is $248,000-$349,000 + 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.
Qualifications
Minimum qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience in software development and building and scaling large-scale infrastructure, distributed systems, or networks. 5 years of experience in a technical leadership role; overseeing projects, with 5 years of experience in a people management, supervision/team leadership role. 3 years of deep technical expertise in AI/ML infrastructure.Preferred qualifications: Master’s degree or PhD in Engineering, Computer Science, or a related technical field. 3 years of experience with AI/ML inference stack.
Extended Qualifications
Bachelor's degree or equivalent practical experience. 8 years of experience in software development and building and scaling large-scale infrastructure, distributed systems, or networks. 5 years of experience in a technical leadership role; overseeing projects, with 5 years of experience in a people management, supervision/team leadership role. 3 years of deep technical expertise in AI/ML infrastructure.Check out other jobs at Google.