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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.

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.

Our Data Science team leads data-motivated decisions across Waze's core functional areas, including the Waze Map and Map Editor, Advanced Guidance and Voices, Growth and Strategy, User Communications and more. The team members are embedded within the Waze development Squads. We define data requirements and analytics strategies, execute experiments, deliver in-depth analyses and provide actionable recommendations. The teams contribution is crucial for the effective development and safe landing of the new Waze features and help guiding the overall product strategy.

We are responsible for the research and development of advanced experimentation and Causal Analysis infrastructures to measure, understand and attribute features impact. We also own a comprehensive Data Warehouse, providing essential dashboards and analytics tools, including Gen-AI agents, to empower both Data Scientists and stakeholders throughout the organization.

Responsibilities
Develop and implement Measurement Methodologies and Evaluation Frameworks. Assess the performance, accuracy and groundedness of AI Agents, including the automated generation of synthetic training and evaluation data.
Work with various teams including software developers, data engineers and product managers, to define the requirements and implement Gen-AI models and solutions to drive innovation.
Translate technical concepts and investigative findings into clear, actionable insights for both technical and non-technical stakeholders.
Lead the design, development and deployment of Generative AI Agents for conversational driving-related experiences and scaling the ingestion, annotation and utilization of user generated contect and geospatial data feeds.

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.

Google System Infrastructure builds the cloud for Google services and for Google Cloud customers, by solving business test of performance, cost, and scale, utilizing hardware, software, and system solutions.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 strategy, identify the platform to validate reasoning components.
Define the test plan and strategy with stakeholders, including sign-off and exit criteria.
Plan and execute the verification of Internet Protocols (IPs) using dynamic verification and formal verification.

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.

Responsibilities
Collaborate with Architecture, Design and Verification teams to develop new product bring-up, validation, characterization, and qualification strategies and manufacturing test solutions for new High Performance Computing (HPC) products in advanced process technologies.
Verify test solutions on pre-silicon models (simulation or emulation) and develop ATE test modules, DC tests, binning, production and characterization flows.
Develop and validate test programs on ATE platforms for New Product Integration (NPI) in preparation for High Volume Manufacturing (HVM), working with ATE vendors.
Support product sustainability, including volume data analysis of screening and characterization data, test time and yield improvements, assess test escapees and Return Merchandise Authorizations (RMAs), localize failures, implement containment measures and partner with design, manufacturing, quality and reliability teams to root cause and implement corrective actions.
Develop tools, flows and methodologies to continuously improve and automate the testing.

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.

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 Design Verification Engineer, you will work as part of a Research and Development team building 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 with design and verification engineers in active projects and perform verification. You will be responsible for 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 fully 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 SystemVerilog Assertions (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.
Apply 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.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 execute comprehensive validation plans for Google's custom silicon, covering functional, performance, power, and reliability aspects.
Design and build scalable validation test infrastructure, including hardware setups, software frameworks, and automation tools on Emulation or FPGA platforms.
Lead the debugging and resolution of silicon issues, collaborating with cross-functional teams such as design, architecture, software, and firmware.
Analyze validation data to identify trends, root causes, and opportunities for improvement in silicon quality and reliability.
Build and mentor a high-performing team of silicon validation engineers, fostering a culture of collaboration, innovation, and technical excellence.

The Personalized Experience team focuses on providing Waze drivers with a personalized, contextual, and timely routing experience. The team is part of the Waze Data Science group.


Responsibilities
Manage feature engineering, model evaluation and error analysis, data processing and pipelines, model tuning, monitoring and dashboards.
Work with product managers, software developers and QA to define requirements, formulate success metrics, and lead experimentation.
Use data to help products shape the future of Waze and drive innovation, provide insights on user behavior, and help Engineers and QA detect and solve problems.
Work with GCP, Vertex AI, Python, Scikit-learn, TensorFlow, Airflow/Composer, Python, Looker.

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.

The Growth and Notifications Team (GaNT) makes it easy for Google products to acquire, engage, retain, and ultimately delight our users by enabling high-quality notifications and helping drive growth across the Google ecosystem.

As a Software Engineer, you will join our mobile team (iOS) in the notifications space. You are passionate about mobile applications, engineering infrastructure, and enabling Google to manage and optimize our notifications, then consider the Growth and Notifications Team (GaNT) SDK team. We are responsible for receiving, rendering, analyzing and optimizing notifications sent to mobile devices by Google products. We work closely with many of Googles first-party apps and have significant exposure to iOS teams across Google.

The Core team builds the technical foundation behind Googles flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Googles products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.

Responsibilities
Write product or system development code.
Participate in, or lead design reviews with peers and stakeholders to decide amongst 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 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.

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.

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
Design, develop, and maintain CAD tools and scripts to automate and streamline design tasks, verification processes, and data analysis.
Administer and optimize the front-end compute environment, ensuring reliability, performance, and scalability.
Provide technical support and training to Design and Verification teams on the use of CAD tools, scripts, and the compute environment.
Identify opportunities to enhance front-end development workflows, implement improvements, and document best practices.
Work closely with design, verification, and CAD teams to understand their needs, gather requirements, and deliver effective solutions.

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, with your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

Google Cloud accelerates every organizations ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Googles cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
Write product or system development code.
Participate in, or lead design reviews with peers and stakeholders to decide amongst 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.

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.

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

Waze is where people and technology meet to solve transportation challenges. It's a platform that empowers users to contribute road data and edit Waze maps to improve the way we move about the world. As the social navigation pioneer, Waze leverages mobile technology and a passionate global community to redefine expectations of todays maps.

Responsibilities
Write product or system development code.
Participate in, or lead design reviews with peers and stakeholders to decide amongst 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.