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We're the driving team 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 the formal verification strategy and create the properties and constraints for digital design blocks.
Utilize formal property verification tools combined with formal verification closure techniques to verify properties.
Resolve difficult to verify properties, and contribute improvements to methodologies to enhance formal verification results.
Implement reusable formal verification components.

In this role, you will develop and maintain the data ingestion part of the platform, the part that connects to external sources and extracts the data.Google Cloud accelerates every organizations ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Googles technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
Set and communicate team priorities that support the organization's goals. Align strategy, processes, and decision-making across teams.
Develop the mid-term technical goal and roadmap within the scope of the multiple teams. Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
Design, guide and vet systems designs within the scope of the broader area, and write product or system development code to solve ambiguous problems.
Provide technical leadership on sources projects, involving participating in sessions, creating design documents, and conducting code reviews.
Manage, develop, and mentor a team of skilled engineers, fostering a culture of collaboration and innovation and facilitating their career growth.

As a CPU Workload Analysis Researcher within Google Cloud's MSCA organization, you will be integral to developing silicon solutions powering Google's direct-to-consumer products. You will join a Research and Development team focused on analyzing and profiling workloads requirements within the Google Cloud environment. Your role will involve conducting in-depth research on CPU optimization, feature development, and ML usages over compute platforms, contributing to identifying key areas of investment and future opportunities. This role offers a unique opportunity to perform groundbreaking research with a significant impact on both research methodologies and industry products, within the server chip architecture team. Your work will directly influence the next generation of hardware experiences for millions of Google users and Cloud customers.

The AI and Infrastructure team is redefining whats 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.

Responsibilities
Plan and execute detailed analysis of CPU workloads within the Google Cloud infrastructure, analyze trends and map future requirements.
Collaborate closely with architecture and modeling owners to understand design specifications and identify critical scenarios related to CPU performance and efficiency.
Develop and implement custom workload generation tools and methodologies to simulate real-world usage patterns on Google Cloud platforms.
Analyze the impact of machine learning applications on CPU usage, identifying opportunities for optimization and feature enhancements.
Lead the investigation and development of metrics to measure CPU performance and efficiency, presenting findings to stakeholders and contributing to strategic decisions.