Hardware Systems Quality and Reliability Engineering, University Graduate, PHD, Platforms Engineering

Hardware Systems Quality and Reliability Engineering, University Graduate, PHD, Platforms Engineering corporate_fare Google place Sunnyvale, CA, USA bar_chart Mid Mid Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area. info_outline X This is a specialized role which requires physical interaction with hardware equipment in a simulated data center environment, utilizing Google labs, power, and safety equipment. Regular development and processing of engineering hardware must be performed on site. Willingness to undertake professional travel for up to 20% of the time.

Minimum qualifications:

PhD degree in Electrical Engineering, Computer Engineering, Physics, a related field, or equivalent practical experience. Experience in any one domain of hardware engineering through internships, academic research, or publications (e.g., data center system hardware domains such as semiconductors, PCIe, power electronics, CPU/xPU architectures, networking, embedded systems, and servers.). Experience in data curation, mining/analysis, visualization, and scripting utilizing tools such as SQL, JMP, Python, R, Tableau, or similar.

Preferred qualifications:

Experience in technical project management and effective communication with executive stakeholders. Proficiency in statistical methodologies, predictive modeling, and data visualization techniques. Expertise in quality and reliability engineering roles. Familiarity with fault isolation and other failure analysis methodologies. Track record of providing technical leadership to cross-functional engineering teams through a solution-oriented and pragmatic methodology. About the job The team is responsible for identifying and resolving fleet-wide technical issues, implementing strategic product and methodological enhancements to maximize hardware system reliability, and ensuring efficient deployment and maintenance within data center environments. We conduct analysis of fleet data to address systemic issues and implement preventative measures to ensure long-term stability. 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 $132,000-$189,000 + 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 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 . Responsibilities Collaborate on data center hardware platforms across a wide range of domains, including semiconductors, test, Peripheral Component Interconnect Express (PCIe), power, CPU, xPU, power electronics, and networking. Provide technical leadership by establishing priorities, conducting comprehensive root cause analyses, and resolving complex technical challenges to ensure fleet quality and a stable customer experience. Optimize system health and repairability by improving Mean Time Between Failures (MTBF), managing swap rates, and developing advanced repair strategies. Partner with System Software and Diagnostics/Test teams to enhance the detection, characterization, and resolution of fleet-scale hardware failures. Lead the initiation and implementation of innovative product, process, and tool enhancement projects within complex cross-functional environments and integrate lessons learned from field performance data into New Product Introduction (NPI).