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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.
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 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.
Contribute improvements to methodologies to enhance formal verification results.
Architect and implement reusable formal verification components.

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 Junior SoC Design Verification Engineer, you will develop and execute efficient verification strategies ranging from planning and constrained random testing to debugging and closure while collaborating with engineers to validate digital designs across the life-cycle.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 verification of digital design blocks by understanding specifications and collaborating with design engineers to identify key scenarios.
Develop and refine constrained-random verification environments using SystemVerilog and Universal Verification Methodology (UVM) or formally verify designs using SVA and formal tools.
Identify and define all relevant coverage measures to address design corner-cases.
Debug tests with design engineers to ensure functionally correct design blocks.
Close coverage gaps to identify verification holes and demonstrate progress towards tape-out.

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.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
Help to maintain and upgrade emulation infrastructure and act as a primary interface to emulation vendors.
Explore emulation methodologies, gather feedback from the team, and implement emulation workflows and methodologies.
Create tooling and automation to support emulation Electronic Design Automation (EDA) tools, licensing, and job management in Google infrastructure.
Support emulation team members in debugging hardware, tooling, and project specific issues.
Help bring up external interfaces (e.g., USB, Peripheral Component Interconnect Express (PCIe), Ethernet, etc.) on the emulation platforms, and create test cases for tool issues encountered in the emulation compile and runtime flows.

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.
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.

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
Design, develop, test, deploy, maintain, and improve SOC software modeling and other software tools.
Manage individual project priorities, deadlines, and deliverables.
Collaborate with hardware and software 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.
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
Build C/C++ firmware running on embedded processors with limited memory footprints on the SoCs.
Develop tools to update and debug the firmware, enable emulation, chip bringup, and hardware debugging.
Play key roles in emulation, chip bring up, and SoC deployment, and contribute to all layers of the data center software stack to deploy SoCs to production.
Create code generators to generate C++ code based on hardware specifications.