Minimum qualifications:
- Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
- 13 years of experience in reading/debugging code written in a general purpose coding language (e.g., Java, C, C++, Python, Shell, Go or JavaScript, etc.) and in virtualization and orchestration frameworks.
- Experience troubleshooting and advocating for customer needs, and triaging technical issues across the stack (e.g., hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, performance)
- Experience with Linux/Unix systems and debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
Preferred qualifications:
- Experience working with large-scale distributed systems, and familiarity with common solutions, design patterns, or best practices.
- Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
- Experience with ML frameworks (e.g., TensorFlow, PyTorch), and understanding of the AI/ML training and inference life-cycle.
- Familiarity with containerization and orchestration technologies like Kubernetes or Slurm in an on-prem or cloud environment.
About the job:
Our Solutions Developers for AI Infrastructure own complex customer issues and provide specialized support to other teams. As a part of a global team that provides 24x7 support to ensure customers can seamlessly deploy their AI and ML workloads on AI Infrastructure products, you will ensure we have the expertise, tools, and processes to resolve deep technical issues customers encounter. You will handle customer escalations by combining business acumen with technical skills, develop team members into highly skilled troubleshooting experts who can diagnose a wide variety of issues within the hardware and software boundary within minutes. You will lead operational excellence within the team with a focus on reliable execution, help drive business growth by recognizing and advocating for our customers’ challenges related to AI deployments.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Canada: $174000 - $178000 (CAD) + 20% bonus target + equity + benefits
Learn more about
benefits at Google.
Responsibilities:
- Manage customers' problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity for customer issues on AI/ML infrastructure.
- 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 Development, Sales, and customer organizations to resolve complex deployment and operational obstacles in AI infrastructure environments.
- Work closely with multiple Product and Development teams to find ways to improve the product, and interact with our Site Reliability Developing teams to drive high-quality production.
