Minimum qualifications:
- Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, Physics, or a specialized field (e.g., Optics, Sensors, Audio/DSP, etc.), or equivalent practical experience.
- 1 year of experience working in a hardware engineering technical environment
- Experience with Linux, networking, network troubleshooting, failure diagnosis, data center server, debugging/troubleshooting.
Preferred qualifications:
- Master's degree or PhD in Electrical Engineering, Computer Engineering, Physics, or a related field (e.g., Optics, Sensors, Audio/DSP).
- Experience working within a data center or networking operation center environment.
- Experience with network design, protocols, and troubleshooting.
- Experience with computer systems (e.g., physical, functional, logical, mechanical, electrical, software, thermal, etc.).
- Experience reading and writing code in Python or other scripting language.
As an Hardware Validation Engineer, you will make technical contributions under the scope of a medium-scale design or design validation project with general guidance from managers. You will implement, test, maintain, and contribute to the design of multiple subsystems and will help in developing hardware designs. You will prepare and provide all types of documents including but not limited to concept designs, drawing markup, budget, schedule, design validation plan or results, or factory test and acceptance documents. You will apply standard tools, resources, and processes to solve defined problems within a design project (e.g., modifying an existing design). As you will contribute to cross-project collaborations, you will appropriately share knowledge relevant to well-defined tasks (e.g., communicate objectives, timelines, progress, hurdles, and emergent issues and risks). You will also engage in community contributions to improve and sustain our culture and operations making Google a better place to work. You will support new product engineering and development in Google’s hardware research and development (R&D) labs by helping to design, build, and maintain complex system-level testbeds (think data center-scale).
Our engineering lab team performs work that allows product development teams to focus on development. We have broad general skill sets and take pride in running engineering labs and filling in the gaps between the more narrowly-focused product development teams.
The AI and Infrastructure team is redefining what’s 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.
The US base salary range for this full-time position is $105,000-$151,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about
benefits at Google.
- Help design and build complex system-level testbeds and maintain lab space, tools and infrastructure.
- Work with teams to develop software and hardware systems and develop methodologies and tools to support team members.
- Coordinate the interactions between labs and engineering.
- Anticipate and resolve problems by applying knowledge and skills, escalating design, manufacturing and product test issues to other people within the organization when appropriate.
- Generate implementation plans and provide technical expertise and guidance during deployment activities.
