AI Infrastructure Engineer

Job Summary

To support a growing technology initiative, the full-time AI Infrastructure Engineer will design and operate GPU and accelerator infrastructure for large-scale AI training and inference workloads in a fully remote environment.

Key Responsibilities

• Design and operate GPU and accelerator infrastructure for training and inference across on-prem and cloud-managed services
• Build scheduling and resource-sharing systems to maximize accelerator utilization across teams
• Integrate machine learning frameworks into a unified platform and maintain high-performance storage systems

Required Qualifications

• Bachelor's or Master's degree in Computer Science or a related field
• Six or more years of experience in infrastructure, platform, or HPC engineering
• Hands-on experience operating GPU clusters or large-scale ML training infrastructure
• Strong proficiency in Python and at least one systems language such as Go or C++
• Deep understanding of distributed training and accelerator architectures