דרושים » פיתוח תוכנה » system Engineer for Naval Systems

Google's custom-designed machines make up one of the largest and most powerful computing infrastructures in the world. The Hardware Testing Engineering team ensures that this cutting-edge equipment is reliable. In the R&D lab, you design test equipment for prototypes of our machinery and develop the protocols used to scale these tests for the entire global team. Working closely with design engineers, you give input on designs to improve our hardware until you're sure it meets Google's standards of quality and reliability.
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
Design, develop, and maintain CAD tools and scripts to automate and streamline design tasks, verification processes, and data analysis.
Administer and optimize the front-end compute environment, ensuring reliability, performance, and scalability.
Provide technical support and training to Design and Verification teams on the use of CAD tools, scripts, and the compute environment.
Identify opportunities to enhance front-end development workflows, implement improvements, and document best practices.
Work closely with design, verification, and CAD teams to understand their needs, gather requirements, and deliver effective solutions.

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
Write and test product or system development code.
Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Design and implement solutions in one or more specialized Machine Learning (ML) areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.