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We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Responsibilities
Define the block-level design document (e.g., interface protocol, block diagram, transaction flow, pipeline, etc.).
Perform Register-Transfer Level (RTL) coding (coding and debug in Verilog, SystemVerilog), function/performance simulation debug, and Lint/CDC/FV/UPF checks.
Participate in synthesis, timing/power closure activities.
Participate in test plan and coverage analysis of the block and SoC-level verification.
Communicate and work with multi-disciplined and multi-site teams.

In this role, you will be part of a team developing Application-specific integrated circuits (ASICs) used to accelerate networking in data centers. You will have multiple 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 also be responsible for performance analysis for an end-to-end networking stack using your knowledge.
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
Lead an ASIC subsystem.
Understand how it interacts with software and other ASIC subsystems to implement data center networks.
Define hardware/software interfaces. Write micro architecture and design specifications.
Define efficient micro-architecture and block partitioning/interfaces and flows.
Collaborate closely with software, verification, and physical design stakeholders to ensure the designs are complete, correct, and performant.

As a Senior Design Verification Engineer, you will be a part of Research and Development team to verify digital designs, develop constrained-random test environments and drive system testing to closure. You will collaborate with design and verification teams, manage the verification life-cycle and uncover bugs through corner-case testing.The AI and Infrastructure team is redefining whats possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Responsibilities
Plan and execute the verification of digital design blocks by understanding specifications and working with design engineers to define key verification scenarios.
Develop and refine random verification environments using SystemVerilog/UVM or Specman to ensure effective test coverage.
Define and implement various coverage measures to capture stimulus and corner-case scenarios.
Collaborate with design engineers to debug tests and ensure functional correctness of design blocks.
Drive coverage analysis to identify verification gaps and demonstrate progress towards tape-out.

Were seeking a motivated, detail-oriented Front-End Engineer to craft seamless, high-performance experiences across browsers and WebViews. At Unity, youll work in a dynamic environment that brings together web front ends, backend services, and machine learning into a unified, complex system. This is an ideal role for engineers eager to make a substantial impact on a technically challenging product in a fast-paced setting.
What you'll be doing
Build and maintain React-based SPAs and NX-powered micro frontends
Implement high-quality TypeScript, HTML, and CSS
Translate Figma designs into reusable, responsive components and design systems
Optimize for WebView and multiple browsers, ensuring cross-platform consistency
Collaborate with product/design to iterate quickly and ship value

What you'll be doing
Design Data-Native Cloud Solutions - Design and implement scalable data infrastructure across multiple environments using Kubernetes, orchestration platforms, and IaC to power our AI, ML, and analytics ecosystem
Define DataOps Technical Strategy - Shape the technical vision and roadmap for our data infrastructure capabilities, aligning DevOps, Data Engineering, and ML teams around common patterns and practices
Accelerate Data Engineer Experience - Spearhead improvements to data pipeline deployment, monitoring tools, and self-service capabilities that empower data teams to deliver insights faster with higher reliability
Engineer Robust Data Platforms - Build and optimize infrastructure that supports diverse data workloads from real-time streaming to batch processing, ensuring performance and cost-effectiveness for critical analytics systems
Drive DataOps Excellence - Collaborate with engineering leaders across data teams, champion modern infrastructure practices, and mentor team members to elevate how we build, deploy, and operate data systems at scale

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 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, supporting the hardware and lab bring up, and verifying our ASIC systems.

The AI and Infrastructure team is redefining whats possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

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 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.

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
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.