AI Infrastructure Solutions Engineer

Jobs in JS; Kirkland (WA); On-site; USD 102,000 - 144,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

Google Cloud is seeking Solutions Engineers for AI Infrastructure to own complex customer issues and provide expert support across teams. You will troubleshoot hardware and software, networking, and Linux administration to enable AI/ML workloads on Google Cloud AI Infrastructure products.

You will work with Engineering, Sales, and customer organizations to resolve deployment obstacles, develop diagnostic tools, and contribute to product improvements.

Qualifications

• Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
• Experience reading/debugging code in a general purpose language and in virtualization/orchestration frameworks.
• Experience troubleshooting and triaging customer issues across the stack.
• System administrator level experience with Linux/Unix and debugging on enterprise-grade servers.

Responsibilities

• Diagnose and resolve customer issues on AI/ML infrastructure through tools and new investigation methods.
• Build understanding of AI/ML workloads and hardware architectures by debugging, reproducing, and root-cause analysis.
• Consult with Engineering, Sales, and customer teams to resolve deployment and operational challenges.
• Collaborate with Product and Engineering teams and SRE to improve products and production quality.
• Be available for non-standard hours and weekend shifts as needed.

Skills

Code reading/debugging

Troubleshooting

Linux system administration

Hardware/software boundary debugging

Education

Bachelor's degree in STEM or equivalent

Tools

Kubernetes

Slurm

Job description

Google Cloud is seeking Solutions Engineers for AI Infrastructure to own complex customer issues and provide expert support across teams. You will troubleshoot hardware and software, networking, and Linux administration to enable AI/ML workloads on Google Cloud AI Infrastructure products.

You will work with Engineering, Sales, and customer organizations to resolve deployment obstacles, develop diagnostic tools, and contribute to product improvements.