Technical Program Manager III, GPU Infrastructure Reliability, Google Cloud

Google•Kirkland, WA

2d•$163,000 - $237,000

About The Position

To empower AI innovation by accelerating the delivery, cloud-based accelerator (GPU) NPIs built into large-scale supercomputer clusters, including next-gen cross-functional development, customer and vendor partnerships, and ML workload monitoring and diagnostic tooling. As a GPU Technical Program Manager for Google Cloud’s AI and Computing Infrastructure team, you will be at the forefront of AI innovation, leading the end-to-end development and delivery of next-generation Cloud GPU products from initial concept to full-scale production. You will take charge of software qualification and release strategies for AI hypercompute clusters, collaborating deeply with engineering, product, and capacity planning teams to align customer and business priorities. Beyond managing critical escalations and mitigating risks, this is a unique opportunity to shape cross-functional initiatives alongside Application Centric Infrastructure (ACI) leadership and Technical Program Managers (TPMs) across the broader organization to streamline customer onboarding and scaled support for our largest, most complex Cloud ML solutions. The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world. We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

Requirements

Bachelor's degree in a technical field, or equivalent practical experience.
5 years of experience in program management.
Experience with infrastructure reliability.
Experience with GPUs or GPU Systems.

Nice To Haves

5 years of experience managing cross-functional or cross-team projects.
5 years of experience in technical program management, with a focus on software engineering and ML infrastructure projects.
Knowledge of software development, distributed systems, and ML infrastructure or GPU systems.
Ability to think critically and solve problems.
Excellent project management skills, and experience with project planning, execution, and risk management.
Excellent communication and collaboration skills, with the ability to build relationships and influence across all levels of the organization.

Responsibilities

Lead the end-to-end development, project planning, and delivery of next-gen AI Infra GPU products from concept to production.
Lead software qualifications, release strategy, and test infrastructure management for AI hypercompute clusters.
Manage escalations and critical incidents while proactively identifying and mitigating risks that could impact project success.
Coordinate with TPMs in AI2 (e.g., ACI, Platforms, and CSCO) and ACI leadership on cross-functional initiatives related to AI Infra customer onboarding and production support.
Participate in the development of core management software, monitoring, and diagnostic tooling for scalable Cloud ML solutions.