Be part of a diverse 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 be part of a team developing Application-Specific Integrated Circuit (ASIC) used to accelerate networking in data centers. You will have dynamic, multi-faceted responsibilities in areas such as project definition, design, and implementation. You will participate in the design, architecture, documentation, and implementation of the next generation of data center accelerators.

You will be responsible for performance analysis for an end to end networking stack using your deep knowledge of RDMA based transports.

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
Participate in evaluation of future ASIC designs and general architecture for executing Googles data center networking roadmap: off-the-shelf components, vendor co-developments, custom designs, and chiplets.
Collaborate in developing new layer protocols for data center networking.
Understand how it interacts with software and other ASIC subsystems to implement groundbreaking data center networks.
Define performance hardware/software interfaces. Write micro architecture and design specifications
Define efficient micro-architecture and block partitioning/interfaces and flows

About the job
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 be part of a team developing Application-Specific Integrated Circuit (ASIC) used to accelerate networking in data centers. You will have dynamic, multi-faceted responsibilities in areas such as project definition, design, and implementation. You will participate in the design, architecture, documentation, and implementation of the next generation of data center accelerators. You will be responsible for performance analysis for an end to end networking stack using your deep knowledge of Remote Direct Memory Access (RDMA) based transports.

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
Participate in evaluation of future ASIC designs and general architecture for executing Googles data center networking roadmap, off-the-shelf components, vendor co-developments, custom designs, and chiplets.
Collaborate to develop new layer protocols for data center networking.
Understand how everything interacts with software and other ASIC subsystems to implement data center networks.
Define performance hardware/software interfaces. Write micro-architecture and design specifications.
Define efficient micro-architecture and block partitioning/interfaces and flows.

Be part of a diverse 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 be part of a team developing Application-Specific Integrated Circuit (ASIC) used to accelerate networking in data centers. You will participate in the design, architecture, documentation, and implementation of the next generation of data center accelerators. You will be responsible for performance analysis for an end to end networking stack using deep knowledge of RDMA based transports.

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
Participate in evaluation of future ASIC designs and general architecture for executing Googles data center networking roadmap, off-the-shelf components, vendor co-developments, custom designs, and chiplets.
Collaborate in developing new layer protocols for data center networking.
Understand how everything interacts with software and other ASIC subsystems to implement groundbreaking data center networks.
Define performance hardware/software interfaces. Write micro-architecture and design specifications
Define efficient micro-architecture and block partitioning/interfaces and 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.
As a Executive CPU Design Verification Engineer, you will work as part of a Research and Development team, and you will build verification components, constrained-random testing, system testing, and verification closure. As part of our server chip design team, you will verify digital designs. You will collaborate closely with design and verification engineers in 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 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/UVM, or Specman.
Identify and write all types of coverage measures for stimulus and corner-cases.
Debug tests with design engineers to deliver functionally correct design blocks.
Lead coverage measures to identify verification holes and to show progress towards tape-out.

Be part of a diverse 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 the DFT Senior Engineer, you will play a crucial role in DFT Architecture and DFT design, and support devices of extreme complexity to production. You will be responsible for providing technical leadership in DFT, developing flows, automation, and methodology, planning DFT activities, tracking the DFT quality matrix throughout the project lifecycle, and providing sign-off DFT to tapeout.

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
Lead and execute activities in the design, implementation, and verification of DFT solutions for large-scale ASICs.
Develop DFT strategy and architecture, including hierarchical DFT, Memory Built-In Self Test (MBIST), and Automatic Test Pattern Generation (ATPG).
Work with other Engineering teams (e.g., Design, Verification, Physical Design) to ensure that DFT requirements are met and mutual dependencies are managed.
Manage the DFT team's workload and deliverables, provide technical leadership and guidance to the team.
Lead DFT execution of a silicon project - planning, execution, tracking, quality, and signoff.

Be part of a diverse 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 work with system teams and the CPU Architecture team to develop an understanding of the CPU, 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. In addition, you will correlate performance projections with measured post-silicon data.

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.

Be part of a team to verify complex digital design blocks at subsystem level or full chip level by fully understanding the design specification and interacting with design engineers to identify key verification scenarios.
Create and enhance constrained-random verification environments using UVM SystemVerilog or create complex multi core based C tests using reusable C test libs.
Identify and write all types of coverage measures for stimulus and 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.

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.

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:
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.

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
Contribute to CPU front-end designs, emphasizing micro-architecture and RTL design for next generation CPU.
Propose performance enhancing micro-architecture features with efficiency in mind. Work with architects and performance teams for trade-off studies.
Deliver designs that meet power, performance, and area (PPA) goals with production quality.
Interpret techniques into design constructs and languages in order to provide guidance to and participate in the performance modeling effort.

Google's custom-designed machines make up one of the largest and most powerful computing infrastructures in the world. The Hardware Testing Engineering team ensures that this cutting-edge equipment is reliable. In the R&D lab, you design test equipment for prototypes of our machinery and develop the protocols used to scale these tests for the entire global team. Working closely with design engineers, you give input on designs to improve our hardware until you're sure it meets Google's standards of quality and reliability.

As a Chip Infrastructure Engineer, you will plan and execute work in an innovative and fast-paced environment, with a focus on infrastructure that enables design and verification teams to produce the chips that power Google's computing needs. You'll be part of the chip infrastructure team responsible for compute, storage, common chip design components, and front-end tool flows.

In this role, you will work with architects, logic designers, and verification engineers to develop flows to build and verify SoC chip designs. Youll also work closely with software, physical design, silicon bring-up and validation teams to enable a successful software integration, implementation, silicon bringup and deliver quality silicon.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 and test product or system development code.
Participate in, or lead design reviews with peers and stakeholders to decide amongs available technologies.
Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.

Be part of a diverse 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
Contribute to CPU frontend designs, emphasizing on microarchitecture and RTL design for the next generation CPU.
Propose performance enhancing microarchitecture features with efficiency in mind. Work with architects and performance teams for trade-off studies. Communicate pros and cons of microarchitecture enhancements. Facilitate final decision making.
Deliver designs meeting Power, performance, and area (PPA) goals with production quality.
Become familiar with techniques for at least one processor functional block. Interpret the techniques into design constructs and languages in order to provide guidance to and participate in the performance modeling effort.