You will:

• Analyze and report on ML resource (compute, storage, accelerators) usage, costs, and efficiency trends across different teams and projects.
• Develop, maintain, and improve dashboards and tools for monitoring key resource metrics and providing actionable insights.
• Identify and investigate opportunities for resource optimization, cost reduction, and performance improvements in ML workflows.
• Support and guide ML engineers and researchers on best practices for resource utilization
• Contribute to the development, documentation, and enforcement of resource management policies and best practices.

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You have:

• Bachelor's degree in Computer Science, Engineering, or related field, and 2+ years equivalent experience
• Experience with distributed systems principles and experience building distributed systems for production environments.
• Solid Python or C++ skills
• Experience monitoring, debugging, and troubleshooting complex distributed systems
• Experience communicating updates and resolutions to customers and other partners

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