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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.
In this role, you will work as part of a Research and Development team. You will build verification components, constrained-random testing, system testing, and verification closure. You will verify digital designs and collaborate 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 life-cycle of verification which can range from verification planning, test execution or collecting, and closing coverage.

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 verification of digital design blocks by 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 Strategic Value Add (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.
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.
In this role, you will help to develop and maintain emulation infrastructure, tools, and workflow methodologies supporting our Application-specific integrated circuit (ASIC) projects. You will provide emulation infrastructure and methodologies for supporting these projects. You will work with other emulation team members as well as designers, verification engineers, and software teams. You will work with with our external vendors, lab support teams, networking and security, and Electronic Design Automation (EDA) tooling and methodology teams to deliver emulation based prototyping capabilities for our ASIC projects. You will also assist in compiling projects specifying our prototyping platforms, debugging issues in both infrastructure and design, assisting in the hardware and lab bring up, and verification of our ASIC systems.

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 in maintaining and upgrading 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 with debugging hardware, tooling, and project specific issues.
Help to bring up external interfaces (e.g., USB, PCIe, Ethernet, etc.) on the emulation platforms, and create standalone test cases for tool issues encountered in the emulation compile and runtime flows.

Research happens at Google everyday, on many different embedded teams throughout the company. Our research reaches the user through both services and products such as Search, Maps, Google Assistant, Google Translate, Google Cloud, and our computing, storage, and networking infrastructure. To achieve this, were working on projects that utilize the latest technologies that push the boundaries of what is possible. At Google, research-focused engineering interns are embedded throughout the company, contributing to the setup of large-scale tests and deploying promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world. From creating experiments and prototyping implementations to designing architectures, research-focused engineering interns work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and more.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

Responsibilities
Participate in research to develop solutions for real-world, large-scale problems.
Research, conceive, and develop software applications to extend and improve on Google's product offering.
Contribute to a wide variety of projects utilizing natural language processing, artificial intelligence, data compression, machine learning, and search technologies.

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 part of our server chip design team, you will use our Application Specific Integrated Circuit (ASIC) design experience to be part of a team that develops the ASIC SoC and SoC IPs from Power-On-Reset (POR) to Production. You will create SoC Level microarchitecture definitions, Register-Transfer Level (RTL) coding and all RTL quality checks. You will also have the opportunity to contribute to Design flow and Methodologies.

In this role, you will collaborate with members of architecture, software, verification, power, timing, synthesis design for testability (dft) etc. You will face technical issues and develop/define design options for performance, power and area.

The ML, Systems, and 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 microarchitecture level design document such as interface protocol, block diagram, transaction flow, pipeline etc.
Perform RTL development (e.g., coding and debug in Verilog, SystemVerilog).
Perform 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.