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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.