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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.

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.

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
Define, design, and implement key components, built from the grounds-up.
Participate during the ramping up of the project, and influence critical architecture and design decisions.
Work with peers from other aspects of the product development lifecycle, including all filesystem engineering teams, product management, program management, SRE, UX/UI.
Work with product and customers, to best fit future requirements, developing code primarily in C++.

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.

As an SoC Design Verification Engineer, you will work as part of a Research and Development team, and your responsibilities will include building verification components, constrained-random testing, system testing, and verification closure. As part of our server chip design team, you will use your design and verification expertise to verify complex digital designs. You will collaborate closely with design and verification engineers in active projects and perform verification. Using your UVM and SystemVerilog coding and problem-solving skills, you'll build efficient and effective constrained-random verification environments that exercise designs through their corner-cases and expose all types of bugs. You will be responsible for the full lifecycle 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
Verify designs using verification techniques and methodologies.
Work cross-functionally to debug failures and verify the functional correctness of the design.
Provide test plans, including verification strategy, environment, components, stimulus, checks, and coverage, and ensure documentation is easy to use.

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

Our team focuses on developing foundation models for remote sensing (i.e., satellite, aerial) imagery. We aim to simplify and enhance various remote sensing tasks including land use/land cover segmentation, object detection, and change detection for use by Google teams and external partners. We also investigate natural language interfaces for remote sensing imagery through vision-language models and tasks such as captioning and visual question answering.

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
Explore research directions, generate hypotheses and perform rigorous experimentation in several sub-domains (e.g., pre-training recipes, multi-modality, temporal sequences).
Contribute to shaping the team's roadmap, help prioritize research directions, with focus on innovation and usability.
Work with other researchers across Google to connect multiple geospatial efforts.
Help teams use foundation models and optimize its use on their tasks.
Advise and mentor team members.