דרושים Google Israel

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 use your ASIC design experience to be part of a team that develops the ASIC SoC from POR to Production. Creating SoC Level micro architecture definitions, RTL coding and all RTL quality checks.
You will also have the opportunity to contribute to Design flow and Methodologies.

You will collaborate with members of architecture, software, verification, power, timing, synthesis dft etc. You will face technical tests and develop/define design options for performance, power and area.
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
Define the SoC/Block level design document such as interface protocol, block diagram, transaction flow, pipeline etc.
Perform Register-Transfer Level (RTL) development (e.g., coding and debug in Verilog, System Verilog), function/performance simulation debug and Lint/Cyber Defense Center/Formal Verification/Unified Power Format checks.
Participate in synthesis, timing/power closure, and Application-Specific Integrated Circuit (ASIC) silicon bring-up.
Participate in test plan and coverage analysis of the block and SOC-level verification.
Participate in architecture feedback.

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 Executive CPU Design Verification Engineer, you will be a part of Research and Development team to verify digital designs, develop constrained-randomn 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 rigorous corner-case testing.

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 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.

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.

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 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
Create helpful user-facing channels and cross-product experiences which drive ecosystem adoption, and add value to users across iOS, Android and desktop.
Build native iOS offering, including experiences on iPhones focused on increasing engagement with Google products and features and incorporating the latest trends in iOS development and capabilities into Googles apps.
Increase effectiveness of existing products, improving data analytics pipelines, machine learning (ML) capabilities, experimentation capabilities, alerting, and campaign management.
Improve products through UX improvement, improving latency and product quality, and experimentation related to content improvement.
Focus on iOS technologies which may also include some server-side work, including processing and analyzing data in order to draw metrics-focused conclusions.

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.
Resolve difficult to verify properties, and 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.
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.

Waze is searching for an exceptional Engineering Manager to lead our Personalization and Guidance team. In this pivotal role, you'll be at the forefront of shaping the future of core Waze features, directly influencing critical user experiences that impacts people daily.

As an Engineering Manager at Waze, you'll bring not only your technical expertise to lead major projects but also your passion for developing and mentoring a high-performing team. You'll optimize your own contributions while empowering your team to optimize theirs. You'll drive project goals, contribute significantly to our product strategy, and foster an environment where your team thrives.

Our teams operate with incredible scale and speed. Waze R&D thrives on collaboration, with innovative developers and designers working closely in small, agile groups. You'll work side-by-side with Product and UX in a fast-paced, creative atmosphere, focused on solving problems and building products. If you're passionate about Waze, its community, and constantly exploring new development platforms, functionalities, and APIs, this is the place for you.Waze R&D is all about teamwork. The most innovative developers and designers work together in small groups to build products that are used by millions. Engineers work side by side with Product and UX in a fast, creative atmosphere with minimal documentation. Our team members are self-sufficient and problem solvers. We are looking for people who are passionate about Waze, its community and who are always one step ahead in development platforms, new functionality and APIs.
Responsibilities
Drive the strategic definition and execution of the new Personalization and Guidance capabilities, transforming early-stage concepts into impactful product and engineering solutions. Lead the Personalization and Guidance Engineering team, driving technical strategy and execution.
Lead, mentor, and coach engineers, fostering their professional growth and elevating the team's overall capacity. Collaborate with Product, UX, and Data Science partners to define roadmaps and deliver reliable features.
Partner with cross-functional stakeholders across engineering, data science, product management, and leadership to define and align on future goals for personalization and guidance capabilities. Contribute to product strategy as a leader within the Adaptive Experience Group.
Collaborate with peers to shape the strategic roadmap and drive the execution of the group's ideas. Oversee the design, development, and deployment of features that enhance user personalization and guidance within the Waze app.

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 work with system teams and the CPU Architecture team to develop an understanding of the CPU, 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. In addition, 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
Design, develop, test, deploy, maintain, and improve Central Processing Unit (CPU) software modeling and other software tools.
Manage individual project priorities, deadlines, and deliverables.
Collaborate with hardware and software CPU architecture teams, SOC performance modeling team, and other Google Software teams.

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.