Minimum qualifications:

• Bachelor's degree in a technical field, or equivalent practical experience.
• 8 years of experience in program management.
• 8 years of experience with demand forecasting, capacity planning, or capacity management within a cloud environment.

Preferred qualifications:

• Master's degree and 10 years of relevant industry experience.
• 8 years of experience managing cross-functional or cross-team projects.
• Experience on implementation of capacity planning and resource governance for cloud infrastructure.

About the job

A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.

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.

Responsibilities

• Lead Technical Program Manager (TPgM) to deliver an automated solver solution to enable complex supply/demand matching scenarios. This will be the foundational capability in which Google leadership will make decisions based on scenarios modeled under this capability.
• Lead complex, cross-functional programs related to ML Fleet capacity management, including the design, update, and maintenance of ML Fleet's cluster-level allocation plan of record.
• Drive the development, implementation, and ongoing maintenance of fleet-wide accelerator and auxiliary resource usage metrics, policies, and robust governance frameworks.
• Identify gaps and drive initiatives to improve existing tooling and processes, enhancing the efficiency, agility, and responsiveness of ML capacity allocation and management.
• Partner with key stakeholders including ML Strategy and Allocation (MLSA), Product Area Resource Management Teams (PARMs), Capital Engineering, Supply teams, tooling engineering and system infrastructure SREs.