Technical Program Manager II, Compute Resource Planning, Google Research

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.

Google Research advances the state-of-the-art in Computer Science and Artificial Intelligence to power Google's current and future products. Within Research, the Compute Planning Strategy & Operations (CPSO) team enables seamless scientific discovery and high-performance computing by delivering scalable compute resource infrastructure, automated allocation platforms, and capacity planning frameworks for researchers across Alphabet.

CPSO is Google Research’s compute resource management team. We drive research forward through automated, friction-free compute stewardship, ensuring resources are collaboratively planned, equitably allocated, and efficiently run. By pairing data-driven planning with operational and infrastructure optimizations, we maximize compute Return on Investment (ROI) and accelerate research velocity

As a Technical Program Manager within the Research CPSO team, you will independently manage compute demand signaling, quota allocation cycles, and resource utilization for assigned Research verticals. Operating with minimal day-to-day supervision on a 1–2 quarter horizon, you will bridge the gap between Research Scientists, Engineering Leads, Product Area Resource Managers (PARMs), and Site Reliability Engineering (SRE).

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Run recurring compute resource planning and quota allocation cycles for assigned Research verticals, aligning capacity with research project milestones.
• Gather and analyze inorganic and organic compute demand signals from Research and Engineering teams, establishing data-backed growth forecasts and resource prioritization models.
• Design, automate, and maintain SQL-based dashboards and alerting systems (e.g., Plx/Dashboards) to track pool utilization, quota headroom, and capacity efficiency.
• Leverage AI and partner with Software Engineer and SRE teams to set up and enhance automated resource management tooling, optimizing scheduler queues to eliminate manual allocation workflows.
• Act as the primary operational liaison between Research Scientists, PARMs, and infrastructure partners, facilitating proactive communication on capacity availability and maintenance schedules.

Minimum qualifications:

• Bachelor's degree in a technical field, or equivalent practical experience.
• 2 years of experience in program management.
• Experience with capacity planning.
• Experience with Data Analysis.

Preferred qualifications:

• 2 years of experience managing cross-functional or cross-team projects.
• Experience querying structured datasets using SQL and developing operational dashboards for reporting and metrics tracking.
• Experience with compute resource provisioning, capacity allocation, or job scheduling/queueing systems.
• Experience working with large-scale distributed computing systems, container orchestration, or cluster scheduling environments (e.g., Kubernetes).
• Experience translating ambiguous stakeholder capacity requests into structured allocation models and data-backed forecasts.
• Experience driving process improvements and workflow automation across technical and research engineering teams.