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Job Details
Posted date: Dec 11, 2025
Location: Seattle, WA
Level: Director
Estimated salary: $298,500
Range: $248,000 - $349,000
Description
Define and drive the long-term technical outlook, strategy, and roadmap for critical software systems that manage Alphabet's ML fleet. This includes capacity management for all ML resources such as TPUs, GPUs, compute, storage, and networking. Act as the Technical Lead for the internal Capacity Management Business team within ML Fleet, providing technical direction, mentorship, and guidance to build and evolve our capacity management solutions from operations to robust engineered solutions. Collaborate closely with engineering partners (e.g., Onefleet, Spatial Flex, Operational Data Store (ODS)) to design and deliver joint engineered solutions to our customers. 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.Site Reliability Engineering (SRE) combines software and systems engineering to build and run large-scale, massively distributed, fault-tolerant systems. SRE ensures that Google Cloud's services—both our internally critical and our externally-visible systems—have reliability, uptime appropriate to customer's needs and a fast rate of improvement. Additionally SRE’s will keep an ever-watchful eye on our systems capacity and performance.
Much of our software development focuses on optimizing existing systems, building infrastructure and eliminating work through automation. On the SRE team, you’ll have the opportunity to manage the complex challenges of scale which are unique to Google Cloud, while using your expertise in coding, algorithms, complexity analysis and large-scale system design. SRE's culture of intellectual curiosity, problem solving and openness is key to its success. Our organization brings together people with a wide variety of backgrounds, experiences and perspectives. We encourage them to collaborate, think big and take risks in a blame-free environment. We promote self-direction to work on meaningful projects, while we also strive to create an environment that provides the support and mentorship needed to learn and grow. As a Senior Staff Software Engineer in the ML Fleet Systems team, you will play a critical role in shaping the future of how Google manages its massive and rapidly growing ML infrastructure. You will be a technical luminary, responsible for the architecture, design, and implementation of systems and strategies that ensure the scalable, reliable, and efficient deployment and consumption of ML resources. You will handle ambiguous, high-impact problems, and your work will influence teams across organizational boundaries.
Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
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 in Computer Science, a related field, or equivalent practical experience.8 years of experience with software development in one or more programming languages.
4 years of experience leading projects, and providing technical leadership. 3 years of experience in designing, analyzing, and troubleshooting distributed systems.
Preferred qualifications: Master's degree or PhD in Computer Science, or a related technical field. Experience with infrastructure optimization, performance analysis, and cost reduction in large-scale environments. Experience with colossus and other relevant Google storage systems (e.g., Bigtable, Spanner, Woodshed). Understanding of resource management systems (e.g., Borg, Kubernetes, Flex), cluster management, and scheduling algorithms. Familiarity with Machine Learning hardware accelerators (e.g., TPUs, GPUs) and their lifecycle management. Excellent communication and collaboration skills, with the ability to build consensus across organizational boundaries.
Extended Qualifications
Bachelor’s degree in Computer Science, a related field, or equivalent practical experience.8 years of experience with software development in one or more programming languages.
4 years of experience leading projects, and providing technical leadership. 3 years of experience in designing, analyzing, and troubleshooting distributed systems.
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