Staff Software Engineer, Persistent Disk, Capacity

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

The PD Capacity space delivers the models and systems that guarantee sufficient resources for Persistent Disk (PD), enabling us to meet obtainability and performance SLOs while maintaining low costs. This is a critical component of making block storage (Persistent Disk/Hyperdisk) a foundational cloud differentiator and accelerating the growth of AI and non-AI workloads. Simply put, enabling AI workloads starts with ensuring a disk is available to boot accelerators, train models, or run inference.

To achieve this, the team coordinates AI workload co-location between PD and GCE to align cell capacity with demand, secures sufficient resource supply and reservations across all pools (bytes, performance types, compute, and memory), and executes capacity actuation and divestment to continuously maximize efficiency.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge 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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Responsibilities

• Architect and run scalable distributed systems that leverage data-science forecasting models and provide APIs to track capacity and resource availability across PD.
• Provide core services to manage the complete lifecycle of resources, from acquiring underlying infrastructure to divesting unneeded capacity and optimizing high-performance usage.
• Develop robust tenancy protection mechanisms that balance fair resource distribution with the high-scale demands of enterprise and ML workloads.
• Secure and maintain sufficient supply and reservations across all resource pools, including bytes, performance types, compute, and memory.
• Coordinate resource co-location between PD and GCE to guarantee cell capacity directly aligns with evolving AI workload requirements.