Google Senior Software Engineering Manager, ML Fleet Systems

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Job Details

Posted date: Jan 28, 2026

Location: Seattle, WA

Level: Director

Estimated salary: $298,500
Range: $248,000 - $349,000


Description

Define and drive the long-term technical goal, strategy, and roadmap for critical software systems that manage Alphabet's ML fleet. This includes building systems for all ML resources such as TPUs, GPUs, compute, storage, and networking. Collaborate closely with engineering partners (e.g., Onefleet, Spatial Flex, ODS) to design and deliver joint engineered solutions to our customers (Product Areas within Google). Identify, scope, and solve broad and ambiguous challenges that impact the efficiency, reliability, and cost-effectiveness of the entire ML fleet. Turn these challenges into strategic opportunities and actionable plans. Drive significant improvements in ML fleet metrics, such as utilization, scheduling efficiency, and power consumption, through innovative software and system design. Ensure the long-term health, maintainability, and evolution of the software systems underpinning Google's AI/ML development.

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.

Machine Learning (ML) Fleet provides demand forecasts and fulfillment options for Google's ML infrastructure, and delivers fit-for-purpose ML infrastructure on-time, cost-effectively, and at high quality. ML Fleet performs demand and capacity management for Alphabet's ML infrastructure resources across all Product Areas, ensuring those resources are allocated in line with Alphabet-wide ML priorities. ML Fleet's scope includes demand planning, capacity management, and governance of the ML fleet to execute on Google's AI-first strategy across training, serving, and enterprise offerings.

The ML Fleet Systems team’s mission is to make ML demand planning and capacity management efficient, accurate, and auditable through robust and scalable engineered solutions.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

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 programming in C++, Java, Python, Kotlin or Go. 5 years of experience in a technical leadership role. 5 years of experience in a people management or team leadership role. 3 years of experience in designing, analyzing, and troubleshooting distributed systems.

Preferred qualifications: Master's degree or PhD in Computer Science or related technical field. 5 years of experience working in a complex, matrixed organization. Experience with colossus and other relevant Google storage systems (e.g., Bigtable, Spanner, Woodshed). Experience with infrastructure optimization, performance analysis, and cost reduction in large-scale environments. Familiarity with Machine Learning hardware accelerators (e.g., TPUs, GPUs) and their life-cycle management. Understanding of resource management systems (e.g., compute infrastructure, Kubernetes, Flex), cluster management, and scheduling algorithms.

Extended Qualifications

Bachelor’s degree, or equivalent practical experience. 8 years of experience programming in C++, Java, Python, Kotlin or Go. 5 years of experience in a technical leadership role. 5 years of experience in a people management or team leadership role. 3 years of experience in designing, analyzing, and troubleshooting distributed systems.

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