About Google
Learn more about Google. Explore our innovative AI products and services, and how we. Backed by Kleiner Perkins.
About the role
As a Platform Application Engineer (Hardware Engineer), you will be focused on solving customer observations by, driving deep hardware analysis, debug, and issue resolution through to the root cause. You will dive deep into complex technical challenges, troubleshoot critical issues across the platform, and provide resolutions in both short-term and long-term platform solutions. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Bachelor's degree in Computer Science, Management Information Systems, or other technical field, or equivalent practical experience
- 6 years of experience with technical infrastructure (deployment, maintenance, and troubleshooting), and quality and reliability of technical infrastructure
- 6 years of debug or validation experience with CPU, dGPU, or TPU
- 5 years of experience with hardware debug (silicon debug, platform debug, IO interface, or memory analysis)
- Experience debugging technical issues across the stack (hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance)
- Experience with Linux/Unix systems and debugging issues across the hardware/software boundary on enterprise-grade server infrastructure
More about this role
- Manage customer’s 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 understand behaviors.
- Debug platform hardware and silicon-related issues to drive root-cause resolution and develop permanent improvements.
- Drive understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the cause for customer reported issues, and building tools for faster diagnosis.
- Act as a consultant and subject matter expert for internal stakeholders in Engineering and Quality organizations to resolve complex deployment and operational obstacles in AI infrastructure environments.
- Bachelor's degree in Computer Science, Management Information Systems, or other technical field, or equivalent practical experience.
- 6 years of experience with technical infrastructure (deployment, maintenance, and troubleshooting), and quality and reliability of technical infrastructure.
- 6 years of debug or...
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