דרושים » פיתוח חומרה » SoC and IP Design Engineer, Google Cloud

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 System on a Chip (SoC) Design for Test (DFT) Engineer, you will be responsible for defining, implementing, and deploying advanced DFT methodologies for digital or mixed-signal chips. You will define silicon test strategies, DFT architecture, and create DFT specifications for next generation SoCs. You will design, insert, and verify the DFT logic and prepare for post silicon and co-work/debug with test engineers.

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 DFT strategy and architecture (e.g., Memory Built-In Self Test (MBIST), Automatic Test Pattern Generation (ATPG), hierarchical DFT).
Complete all Test Design Rule Checks (TDRC) and design changes to fix TDRC violations to achieve high-test quality.
Insert DFT logic, boundary scan, scan chains, DFT Compression, Logic Built-In Self Test, Test Access Point (TAP) controller, clock control block, and other DFT IP blocks.
Insert and hook up MBIST logic including test collar around memories, MBIST controllers, eFuse logic, and connect to core and TAP interfaces.
Document DFT architecture, test sequences, and boot-up sequences associated with test pins.

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 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'll 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.

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/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 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.

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 CPU Workload Analysis Researcher within Google Cloud's MSCA organization, you will be integral to developing silicon solutions powering Google's direct-to-consumer products. You will join a Research and Development team focused on analyzing and profiling workloads requirements within the Google Cloud environment. Your role will involve conducting in-depth research on CPU optimization, feature development, and ML usages over compute platforms, contributing to identifying key areas of investment and future opportunities. This role offers a unique opportunity to perform groundbreaking research with a significant impact on both research methodologies and industry products, within the server chip architecture team. Your work will directly influence the next generation of hardware experiences for millions of Google users and Cloud customers.

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 and execute detailed analysis of CPU workloads within the Google Cloud infrastructure, analyze trends and map future requirements.
Collaborate closely with architecture and modeling owners to understand design specifications and identify critical scenarios related to CPU performance and efficiency.
Develop and implement custom workload generation tools and methodologies to simulate real-world usage patterns on Google Cloud platforms.
Analyze the impact of machine learning applications on CPU usage, identifying opportunities for optimization and feature enhancements.
Lead the investigation and development of metrics to measure CPU performance and efficiency, presenting findings to stakeholders and contributing to strategic decisions.

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, you will work with system teams and the CPU Architecture team to develop an understanding of the CPU, System on a Chip (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. You will correlate performance projections with measured post-silicon data.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 product or system development code.
Design, develop, test, deploy, maintain, and improve Central Processing Unit (CPU) software modeling and other software tools.
Manage project priorities, deadlines, and deliverables.
Collaborate with hardware and software CPU architecture teams, SOC performance modeling team, and other Google Software teams.

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 Senior SoC Design Verification Engineer, you will work as part of a Research and Development team. You will build verification components, constrained-random testing, system testing, and drive verification closure.

As part of our server chip design team, you will verify digital designs. You will collaborate closely with design and verification engineers on 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, to 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 and UVM, or formally verify designs with SVA and industry leading formal tools.
Identify and write all types of coverage measures for 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.