About Google
Learn more about Google. Explore our innovative AI products and services, and how we. Backed by Kleiner Perkins.
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 Manager (Hardware Engineer), your team will serve as on-site, external-facing trusted advisors to customers. Learn more about benefits at Google . In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
What they're looking for
- Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or IT-related field, or equivalent practical experience
- 8 years of experience with Linux/Unix systems and experience in debugging issues across the hardware/software boundary on enterprise-grade server infrastructure
- 5 years of experience in technical leadership
- 3 years of experience with technical infrastructure (e.g., deployment, maintenance, and troubleshooting), and with quality and reliability of technical infrastructure
- 3 years of debug or validation experience with CPU, dGPU, or TPU
- 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
- Lead a team that will participate in on-call activities, working with the primary responders to resolve system observations. Provide leadership, mentorship, and career development for team members.
- Manage customer problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity on AI/ML infrastructure.
- Work closely with multiple Product, Quality, and Engineering teams to improve the product, and 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 Engineering, Electrical Engineering, Computer Science, or IT-related field, or equivalent practical experience.
- 8 years of experience with Linux/Unix systems and experience...
Browse similar: AI jobs · AI startup jobs · Startup jobs