Technical Program Manager, ML Fleet

Google • Kirkland, WA

1d

About The Position

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. In this role, you will help in driving the governance, operations, and optimization of Alphabet's Machine Learning infrastructure capacity. As ML investments continue to rapidly scale, you will be instrumental in ensuring the efficient allocation, utilization, and agile redistribution of scarce ML resources (accelerators and auxiliary infrastructure) across all product areas (PAs). You will thrive in a changing environment, possessing a technical background in infrastructure, excellent program management skills, and the ability to influence cross-functional stakeholders at all levels. You will contribute to the foundational infrastructure supporting Google's most critical AI/ML advancements.

Requirements

• Bachelor's degree in a relevant technical or engineering field (e.g., Hardware, Computer Systems, Electrical Engineering, or Software Engineering) or equivalent practical experience.
• 8 years of experience in technical program management, including leading the launch of cross-functional programs involving hardware/systems.
• Experience in machine learning infrastructure or program execution.
• Experience with capacity management, supply chain, or demand forecasting processes in a technology context.

Nice To Haves

• MBA or Master's degree in a technical field.
• 8 years of experience managing cross-functional or cross-team projects.
• Experience with Machine Learning infrastructure, accelerators (TPUs/GPUs), or managing AI/ML workloads at scale.
• Experience in defining and implementing governance frameworks or policies for technical resources.
• Experience presenting to executive-level audiences with, excellent communication skills.
• Ability to navigate ambiguity, influence without direct authority, and drive consensus across various technical and non-technical teams.

Responsibilities

• Lead 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 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 closely with key stakeholders including ML strategy and allocation, product area resource management teams, capital engineering, supply teams, tooling engineering, and system infrastructure site reliability engineers (SREs).
• Manage communications and escalations related to ML resource allocation, performance, and shifts for product areas and other partners.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees