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In this role, you will verify digital designs. You will collaborate closely with design and verification engineers on projects and perform direct verification. You will build efficient and effective constrained-random verification environments that exercise designs through their corner-cases and expose all types of bugs. You will manage the full life-cycle of verification, which can range from verification planning, test execution, to collecting and closing coverage.

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 the verification of digital design blocks by fully understanding the design specification and interacting with design engineers to identify important verification scenarios.
Create and enhance constrained-random verification environments using SystemVerilog and Universal Verification Methodology (UVM) or formally verify designs with SystemVerilog Assertions (SVA) and industry leading formal tools.
Identify and write all types of coverage measures for corner-cases.
Debug tests with design engineers to deliver functionally correct design blocks.
Close coverage measures to identify verification holes and to show progress towards tape-out.

As a Senior Design Verification Engineer, you will be a part of Research and Development team to verify digital designs, develop constrained-random test environments and drive system testing to closure. You will collaborate with design and verification teams, manage the verification life-cycle and uncover bugs through corner-case testing.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 the verification of digital design blocks by understanding specifications and working with design engineers to define key verification scenarios.
Develop and refine random verification environments using SystemVerilog/UVM or Specman to ensure effective test coverage.
Define and implement various coverage measures to capture stimulus and corner-case scenarios.
Collaborate with design engineers to debug tests and ensure functional correctness of design blocks.
Drive coverage analysis to identify verification gaps and demonstrate progress towards tape-out.

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.

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 the verification of digital design blocks by fully understanding the design specification and interacting with design engineers to identify important verification scenarios.
Create and enhance constrained-random verification environments using SystemVerilog and Universal Verification Methodology (UVM), or formally verify designs with SystemVerilog Assertion (SVA) and industry leading formal tools.
Identify and write all types of coverage measures for corner-cases.
Debug tests with design engineers to deliver functionally correct design blocks.
Close coverage measures to identify verification holes and to show progress towards tape-out.

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 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.

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.