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About the role
Our AI Infrastructure Engineering Support team is dedicated to ensuring our customers get the most out of their Google Cloud hardware investment. As a Field Application Engineer (Hardware Engineer), you will be an on-site, external-facing trusted advisor to customers, driving hardware analysis, debug, and issue resolution. You will do in-depth research into complex technical issues, troubleshoot critical issues across the platform, and provide expert solutions that help customers innovate with confidence.
What they're looking for
- Bachelor's degree in Computer Science, Management Information Systems, a related technical field, or equivalent practical experience
- 2 years of debug or validation experience with CPU, dGPU, or TPU
- 2 years of experience with technical infrastructure (deployment or maintenance, and troubleshooting), and with quality and reliability of technical infrastructure
- 2 years of experience with hardware debug (e.g., silicon, platform, IO interface, or memory analysis)
- Experience with Linux/Unix systems and debugging issues across hardware/software boundary on enterprise-grade server infrastructure
- Experience troubleshooting and triaging technical issues across the stack (e.g., hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance)
More about this role
- Participate in on-call activities and manage server and data center CPU- and TPU-based activities, working with primary responders to resolve customer system observations.
- Manage customers' problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity on AI/ML infrastructure.
- Work closely with Product, Quality, and Engineering teams to improve the product. Interact with our Site Reliability Engineering (SRE) teams to drive high-quality attainment.
- Develop an in-depth understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the root cause for customer-reported issues, and building tools for faster diagnosis.
- Act as a consultant and subject matter expert for internal stakeholders in Engineering, Sales, and customer organizations to resolve complex deployment and operational obstacles in AI infrastructure environments.
- Bachelor's degree in Computer Science, Management Information Systems, a related technical field, or equivalent practical experience.
- 2 years of debug or validation experience with CPU, dGPU, or TPU.
- 2 years of experience with technical...
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