AI Infrastructure Engineer

Job Summary

To support large-scale AI training and inference workloads, the full-time AI Infrastructure Engineer will design and operate GPU infrastructure, build resource-sharing systems, and integrate various ML frameworks, all while working remotely.

Key Responsibilities

• Design and operate GPU and accelerator infrastructure for training and inference across on-prem and cloud environments
• Build scheduling and resource-sharing systems to maximize accelerator utilization for multiple teams
• Implement high-performance storage systems and data pipelines to ensure efficient data flow for AI workloads

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