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Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Kirkland, WA, USA; Seattle, WA, USA; Sunnyvale, CA, USA.

Minimum qualifications:

• Bachelor's degree in a technical field, or equivalent practical experience.
• 8 years of experience in program management.
• 8 years of experience in project management, change management, stakeholder alignment, and execution.
• 5 years of experience in demand planning, forecasting, technical program management, supply chain management, business analytics, or a similar role (for hardware infrastructure, particularly for compute, storage, networking, or specialized accelerators (GPUs, TPUs)).

Preferred qualifications:

• 8 years of experience managing cross-functional or cross-team projects.
• Experience in data manipulation and analysis using tools such as SQL, Python (with libraries like pandas, NumPy, SciPy), R, or advanced spreadsheet modeling.
• Experience working with large-scale datasets and data visualization tools (e.g., Tableau, Looker, Google Data Studio).
• Understanding of Machine Learning/Artificial Intelligence (ML/AI) concepts, workloads (training and inference), and their implications for infrastructure.

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.

As a Technical Program Manager (TPM) Demand Planner in ML Fleet, you will play a critical role in forecasting the complex and rapidly evolving demand for Google's ML infrastructure. You will be responsible for developing and maintaining sophisticated demand models, analyzing trends, and collaborating with a wide array of stakeholders across Product Areas (PAs), research, and engineering to gather inputs and validate assumptions. Your work will directly influence multi-billion dollar investment decisions and ensure that the capacity planning and supply chain are aligned with Google's strategic AI objectives. This individual contributor role requires a strong blend of technical understanding, investigative prowess, program management skills, and the ability to navigate a complex, data-rich environment.

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.

The US base salary range for this full-time position is $183,000-$271,000 + 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.

• Implement communications standards across a portfolio of programs including executive and key partner communications.
• Establish a reliable and visible cadence for program reviews, decision-making, prioritization, and Resource Stewardship (effective deployment of machine and people resources) whereby improvements such as efficiency and utilization gains are measurable and the impact can be felt organization wide.
• Lead a governance structure that drives effective executive decision-making. Ensure governance structure effectively exposes and mitigates dependencies.
• Seek out and identify change management opportunities that increase program velocity and which affect multiple teams.
• Define/manage a program portfolio solving problems that target high business impact for the organization and product area.

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