Minimum qualifications:

• Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
• Experience 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 in system administrator with Linux/Unix systems and debugging issues across the hardware/software on enterprise-grade server infrastructure.
• 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).

Preferred qualifications:

• 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 lifecycle.
• Experience working with large-scale distributed systems, and familiarity with common solutions, design patterns, or best practices.
• Familiarity with containerization and orchestration technologies like Kubernetes or Slurm in an on-prem or cloud environment.