דרושים Google Israel

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 Central Processing Unit (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 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 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 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.

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.
Explore new initiatives and improvements on how to get users more engaged with Google products and features.
Scope or create new user facing Growth initiatives, related to users onboarding, education, and better connecting the Google Ecosystem.
Increase robustness of the existing products, improving data analytics pipelines and analytics, ML capabilities, better experimentation capabilities, platformizations, alerting, and improving campaigns management.
Improve and scale products by UX improvement, increase latency and products quality, content improvement and experimentation.

Site Reliability Engineering (SRE) combines software and systems engineering to build and run large-scale, massively distributed, fault-tolerant systems. SRE ensures that Google Cloud's servicesboth our internally critical and our externally-visible systemshave reliability, uptime appropriate to customer's needs and a fast rate of improvement. Additionally SREs will keep an ever-watchful eye on our systems capacity and performance.

Much of our software development focuses on optimizing existing systems, building infrastructure and eliminating work through automation. On the SRE team, youll have the opportunity to manage the complex challenges of scale which are unique to Google Cloud, while using your expertise in coding, algorithms, complexity analysis and large-scale system design. SRE's culture of intellectual curiosity, problem solving and openness is key to its success. Our organization brings together people with a wide variety of backgrounds, experiences and perspectives. We encourage them to collaborate, think big and take risks in a blame-free environment. We promote self-direction to work on meaningful projects, while we also strive to create an environment that provides the support and mentorship needed to learn and grow.

Responsibilities
Improve the life-cycle of services from inception and design, through deployment, operation, and refinement.
Manage support services before they go live through activities such as system design consulting, developing software platforms and frameworks, capacity planning, and launch reviews.
Provide guidance to other team members on managing availability and performance of mission critical services, on building automation to prevent problem recurrence, and on building automated responses for non-exceptional service conditions.
Maintain services once they are live by measuring and monitoring availability, latency, and overall system health, and lead sustainable incident response.
Scale systems sustainably through mechanisms like automation and evolve systems by driving changes that improve reliability and velocity.

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 Google Search, we're reimagining what it means to search for information any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

Responsibilities
Design and implement core features of the native Windows application, focusing on performance, reliability, and user experience.
Integrate the application with Google's backend services and APIs.
Work closely with UX/UI designers to translate mockups and user flows into a polished, native Windows interface.
Collaborate with other Google teams to ensure seamless integration with the Google ecosystem.

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 Application-Specific Integrated Circuit (ASIC) design to be part of a team that creates the System on a Chip (SoC) design cycle from start to finish. You will collaborate with design and verification engineers in projects, creating architecture definitions with Register-Transfer Level (RTL) coding, and running block level simulations. You will contribute in ASIC designs from design specification to production. You will collaborate with members of architecture, software, verification, power, timing, synthesis and more to specify and deliver high quality SoC/RTL. You will also solve technical problems with micro-architecture and solutions, and evaluate design options with 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.
Communicate and work with multi-disciplined and multi-site teams.

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
Address design challenges in high-throughput, large-scale distributed systems built on Google Cloud Platform.
Build the service from the inception, emphasizing on quality and security while ensuring efficient and timely delivery.
Develop expertise working with data technologies (databases, pipelines) and cloud infrastructure.

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 SoC Product Engineer, you will design and build the systems that are the heart of the world's largest and most powerful computing infrastructure. You will develop from the lowest levels of circuit design to large system design and see those systems all the way through to high volume manufacturing and mission-mode operation. You will work to support the machinery that goes into our data centers affecting Google users.

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 implement strategies for high volume manufacturing of SoC products, including troubleshooting, ATE test coverage optimization, DPPM reduction, Test cost reduction, power and performance assurance, and product data integration and correlation between system, ATE, and System Level Test (SLT).
Drive interactions with wafer fabs and OSATs, own and drive checkpoints for key quality metrics.
Drive volume ramp and mass production through test program releases, volume data analytics, lot disposition, extended test time reduction, yield improvement, and RMA handling.
Collaborate with cross-functional teams across the globe including ATE and SLT Test Engineering, Q&R, Packaging, Supplier Management and Operations to build, deploy, and maintain a high volume manufacturing screening solution.
Support setup and maintenance of test, diagnosis, and yield analysis infrastructure, including RMA support.

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 rich 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, 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.