AI Infrastructure Engineer

Job Summary

To support the development of innovative AI solutions, the full-time AI Infrastructure Engineer will design, build, and operate GPU and accelerator infrastructure for large-scale AI training and inference workloads in a 100% remote environment.

Key Responsibilities

• Design and operate GPU and accelerator infrastructure for training and inference across various configurations
• Build scheduling and resource-sharing systems to maximize accelerator utilization across teams
• Integrate machine learning frameworks into a unified platform while ensuring high-performance storage and data pipelines

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, accelerator architectures, and collective communication