Technical Program Manager, NPI, AI/ML, GPU Systems

Minimum qualifications:

• Bachelor's degree in a a technical field, or equivalent practical experience.
• 10 years of experience in Technical Program Management including new product introduction, product life-cycle management, portfolio management, executive communication, and strategy development.
• 8 years of experience with infrastructure work.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 10 years of experience managing complex cross-functional or cross-team projects.
• 5 years of experience with GPU systems and solutions.
• 5 years of experience in a technical leadership role leading project teams and setting technical direction.
• Experience in driving launches, improving productivity and quality standards, resolving problems, identifying trends, determining system improvements, and implementing change.
• Experience managing portfolios and teams delivering outcomes to business in a timely manner.

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 Platforms Infrastructure Engineering Program Management Office is a part of technical infrastructure under Machine Learning, Systems and Cloud AI (MSCA) programs organization and partners with Google Compute Engine (GCE)/Technical Infrastructure (TI) Engineering, Networking, Data center, Supply Chain and Operations teams to deliver a broad product roadmap of AI/ML and standard compute systems, and solutions critical to enabling Cloud (third-party) Infrastructure as a Service (IaaS) business and Google (first-party) services.

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.

The US base salary range for this full-time position is $227,000-$320,000 + 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

• Lead a cross-functional team, spanning all organizational levels and functional areas to develop and deliver programs from inception to production.
• Orchestrate the overall program strategy and drive execution across cross-functional teams.
• Set the direction for a program by outlining goals and objectives, evaluating and supervising multiple projects, organizing cross-project work within the program, and defining program controls/governance/standards.
• Use technical judgment to drive project delivery, technology reviews, issue proposals and build consensus.
• Engage with engineering directors, product leaders and other Technical Program Management (TPM) groups, to streamline processes, simplify execution, manage Objectives and Key Results (OKRs), release on time, bring tooling for efficiencies and help the teams you are engaged with in execution.