Technical Program Manager III, ML Network Deployment, Cloud Networking

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The application window will be open until at least May 22nd, 2025. This opportunity will remain online based on business needs which may be before or after the specified date.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Atlanta, GA, USA; Thornton, CO, USA.

Minimum qualifications:

  • Bachelor’s degree in a technical field, or equivalent practical experience.
  • 5 years of experience in program management.
  • Experience with data center operations, networking deployments or machine learning infrastructure.
  • Experience in new product introduction (NPI).

Preferred qualifications:

  • 5 years of experience managing cross-functional or cross-team projects.
  • Experience with network planning and engineering, including data center network engineering.
  • Knowledge of machine learning product deployments, with experience working with ML in a compressed deployment environment.

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.

The team brings new network solutions that drive innovation, safety, and accelerate business growth. The team is responsible for leading cross-functional collaboration throughout the entire network infrastructure lifecycle. The team focuses on NPIs for Fabric/Cluster Scalability, ML Deployments and ML Enablement work. As new technologies and ML products are developed, the team members evaluate the ability to deploy networks at scale by working across several infrastructure teams. Priorities are aligned across organizations and work streams are managed to make sure hardware software, systems, and workflows come together in the needed time frame.

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.

The US base salary range for this full-time position is $156,000-$229,000 + 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.

Responsibilities

  • Create and drive multi-year roadmaps for deployments for various ML products, Fabric/Cluster upgrades and decom validations on data centers, and colocation locations.
  • Drive dependencies to ensure dependent projects within the portfolio are kicked off in time to support overall ML network roadmap.
  • Lead cross-functional teams and manage network implementations with multiple interdependencies, competing priorities in a compressed timeline while ensuring stakeholders are aware of project status.
  • Lead kickoff and regular project status meetings, keeping upstream and downstream teams at Google updated on program and delivery status.
  • Create and drive new processes/methods where needed and review the work with a wide range of stakeholders.

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