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Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
As a SoC Product Engineer, you will design and build the systems that are the heart of the world's largest and most powerful computing infrastructure. You will develop from the lowest levels of circuit design to large system design and see those systems all the way through to high volume manufacturing and mission-mode operation. You will work to support the machinery that goes into our data centers affecting Google users.

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
Develop and implement strategies for high volume manufacturing of SoC products, including troubleshooting, ATE test coverage optimization, DPPM reduction, Test cost reduction, power and performance assurance, and product data integration and correlation between system, ATE, and System Level Test (SLT).
Drive interactions with wafer fabs and OSATs, own and drive checkpoints for key quality metrics.
Drive volume ramp and mass production through test program releases, volume data analytics, lot disposition, extended test time reduction, yield improvement, and RMA handling.
Collaborate with cross-functional teams across the globe including ATE and SLT Test Engineering, Q&R, Packaging, Supplier Management and Operations to build, deploy, and maintain a high volume manufacturing screening solution.
Support setup and maintenance of test, diagnosis, and yield analysis infrastructure, including RMA support.

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Googles needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, you will work with system teams and the Central Processing Unit (CPU) Architecture team to develop an understanding of the CPU, System on a Chip (SoC), performance metrics, benchmarks/measuring tools, and available optimization knobs. You will define methods and technologies to model CPU performance at different accuracy levels by supporting architectural explorations and decision-making. You will correlate performance projections with measured post-silicon data.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
Write product or system development code.
Design, develop, test, deploy, maintain, and improve Central Processing Unit (CPU) software modeling and other software tools.
Manage project priorities, deadlines, and deliverables.
Collaborate with hardware and software CPU architecture teams, SOC performance modeling team, and other Google Software teams.

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
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 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
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.

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.

In this role, you will use Application-Specific Integrated Circuit (ASIC) design to be part of a team that creates the System on a Chip (SoC) design cycle from start to finish. You will collaborate with design and verification engineers in projects, creating architecture definitions with Register-Transfer Level (RTL) coding, and running block level simulations. You will contribute in ASIC designs from design specification to production. You will collaborate with members of architecture, software, verification, power, timing, synthesis and more to specify and deliver high quality SoC/RTL. You will also solve technical problems with micro-architecture and solutions, and evaluate design options with performance, power, and area.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 SoC/block level design document such as interface protocol, block diagram, transaction flow, pipeline, etc.
Perform Register-Transfer Level (RTL) development (e.g., coding and debug in Verilog, System Verilog), function/performance simulation debug and Lint/Cyber Defense Center/Formal Verification/Unified Power Format checks.
Participate in synthesis, timing/power closure, and Application-Specific Integrated Circuit (ASIC) silicon bring-up.
Participate in test plan and coverage analysis of the block and SOC-level verification.
Communicate and work with multi-disciplined and multi-site teams.