Senior Technical Program Manager, Machine Learning Acceleration

Minimum Qualifications:

• Bachelor's degree in a relevant technical or engineering field (such as Hardware, Computer Systems, Electrical Engineering, or Software Engineering), or equivalent practical experience in these domains.
• 10 years of experience in technical program management or a related engineering/operations role, specifically leading the launch of cross-functional programs involving hardware/systems.
• Experience in Machine Learning infrastructure or program execution.

Preferred Qualifications:

• 5 years of experience in two or more of these areas such as data center design and construction, data center network deployment, ML machine deployment, and turnup.
• Experience collaborating with and influencing stakeholders across multiple organizations and at all levels of leadership.
• Knowledge of the tools and elements of program management and leadership.
• Ability to self-start with a firm sense of accountability and ownership for the end-to-end program life-cycle.
• Ability to shift between detailed execution and analysis and big-picture thinking, prioritization, risk management and communication
• Excellent written and verbal communication skills, with significant experience presenting to executive-level audiences.

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.

As a Senior Technical Program Manager focused on Machine Learning (ML) infrastructure deployment acceleration, you will manage one of the world’s largest ML fleets and drive infrastructure enabling breakthrough AI innovation. You will co-ordinate cross-functional teams to ensure rapid, global deployment of Google's ML infrastructure, delivering to all product areas while meeting critical business timelines. You will own key stakeholders and executive communications, directly impacting velocity and scalability goals of global ML data center deployments. This role offers you the opportunity to enable a more scalable model for ML data center operations and significantly shape the future of AI/ML infrastructure and innovation at Google.

The AI and Infrastructure team works on the world’s toughest problems, redefining what’s possible and the possible easy. We empower Google customers by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Googler Cloud customers, and billions of Google users worldwide. We’re at the center of amazing work at Google by being the “flywheel” that enables our advanced AI models, delivers computing power across global services, and offers platforms that developers use to build services.

In AI and Infrastructure, we shape the future of hyperscale computing by inventing and creating world-leading future technology, and drive global impact by contributing to Google infrastructure, from software to hardware (including building Vertex AI for Google Cloud). We work on complex technologies at a global scale with key players in the AI and systems space. Join a team of talented individuals who not only work together to keep data centers operating efficiently but also create a legacy of driving innovation by building some of the most complex systems technologies.
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.
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 and drive the deployment of Google’s TPU or GPU ML platform deployments across global data centers.
• Deliver deployments in timely fashion, meeting the needs of Google’s product areas.
• Implement best practices for velocity, fungibility and scalability into our ML deployments to meet our ML acceleration goals.
• Build and lead a governance structure that facilitates effective working level and executive alignment, communication, prioritization, risk mitigation, and decision-making.
• Collaborate closely with operational teams to implement key improvements in how our ML data centers operate to enable scalability objectives.