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As a CPU Design Verification Engineer, you will work as part of a Research and Development team building verification components, constrained-random testing, system testing, and verification closure. As part of our server chip design team, you will verify complex digital designs. You will collaborate with design and verification engineers in active projects and perform verification. You will be responsible for the full lifecycle of verification which can range from verification planning, test execution, or collecting and closing coverage.

Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

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 or formally verify designs with SystemVerilog Assertions (SVA) and industry leading formal tools.
Identify and write all types of coverage measures for stimulus and corner-cases.
Debug tests with design engineers to deliver functionally correct design blocks.
Apply close coverage measures to identify verification holes and to show progress towards tape-out.

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.

In this role, you will design, build, and own the foundational systems that empower developers to ship with speed, quality, and confidence. You will be maintaining systems and leading the charge on Waze's technical initiatives.

Waze is where people and technology meet to solve transportation challenges. It's a platform that empowers users to contribute road data and edit Waze maps to improve the way we move about the world. As the social navigation pioneer, Waze leverages mobile technology and a passionate global community to redefine expectations of todays maps.

Responsibilities
Develop and maintain back-end services and libraries, in the Java ecosystem, that form the support of the development environment.
Take ownership of components within technical initiatives, such as the company-wide migration to Google3 or the rollout of new Artificial Intelligence (AI)-powered developer tools.
Deploy and manage mission-critical services on Google Cloud Platform (GCP) using technologies like Kubernetes and Docker, ensuring high availability and performance.
Collaborate with engineering teams across Waze to understand their issues, gather requirements, and deliver solutions that make their workflows efficient.
Work with Java, Python and Google's internal tooling to select the right technology for the job.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Clouds Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

Responsibilities
Define the IP microarchitecture level design document such as interface protocol, block diagram, transaction flow, pipeline etc.
Perform RTL development (coding and debug in Verilog, SystemVerilog).
Conduct function/performance simulation debug and Lint/CDC/FV/UPF checks.
Engage in synthesis, timing/power closure, and ASIC silicon bring-up.
Contribute to verification test plan and coverage analysis of block and SoC-level.

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.