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We're the driving force behind Google's groundbreaking innovations, empowering the development of our 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.

Responsibilities
Plan, coordinate, and deliver custom silicon products.
Assess complexity and scope out the project, generate task lists, build an efficient and effective project timeline and work with the teams to make it reality.
Lead the creation of credible and data-driven schedules and milestones, track the progress, proactively identify potential future issues, and identify mitigations with the various team leaders.
Drive technical, budgetary, and schedule trade-off discussions with cross-functional teams, balancing what is needed with what is possible.
Manage project execution and issues as they arise through design, development, test, manufacturing, deployment and sustaining activities for silicon and hardware products.

In Google Search, we're reimagining what it means to search for information any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

Responsibilities
Write and test product or system development code.
Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Design and implement solutions in one or more specialized Machine Learning (ML) areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.