Senior Technical Program Manager, AI and Infrastructure, TPU

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 AI infrastructure team in Google is looking to build the next generation of AI infrastructure to bring the best of Google to empower Frontier model and AI solution builders to advance the state of the art for AI around the world.

This team is looking for a technical program manager with exposure to fully integrated AI infrastructure systems, from hardware to software design and workload management. We are particularly interested in candidates with experience building very large AI clusters using the latest technologies for AI acceleration and cluster interconnects and networking. We are looking to build the AI infrastructure for the future, so if you are interested in how you could build a brand new product rather than just evolving an existing one, this may be the role you are looking for.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Lead innovation and execution of mission-critical projects, working closely with product teams to understand customer requirements and help relay this information to engineering teams to manage, design, plan, develop and launch technical projects or programs.
• Be the customer interface for the team, interacting with client teams and reviewing new product requirements; track features and dependencies under development for adoption of new technologies and deployment systems.
• Be the effective execution partner by driving projects forward, assessing risks and monitoring tasks.
• Enable cross-functional collaboration across and within the organization. Help be the team and bring better visibility of important efforts.
• Manage strategic programs and tactical day-to-day projects. Help plan infrastructure integration strategies and oversee onboarding of new clients.

Minimum qualifications:

• Bachelor's degree in a technical field, or equivalent practical experience.
  
• 8 years of experience in program management.
  
• Experience working with software and hardware teams in High Performance Computing (HPC) or ML accelerators.

Preferred qualifications:

• 8 years of experience managing cross-functional or cross-team projects.
• Experience with ML techniques and frameworks.
• Experience managing projects on software engineering teams or product management experience, especially innovative/novel engineering programs.
• Familiarity with network, compute and storage at scale.
• Deep understanding of data center terminology and operations.