AI Infrastructure Engineer

Job Summary

Joining a dynamic team, 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 remote setting.

Key Responsibilities

• Design and operate GPU and accelerator infrastructure across on-premises, cloud-managed, and hybrid configurations
• Build scheduling and resource-sharing systems to maximize accelerator utilization for multiple teams
• Integrate various 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 programming language such as Go or C++
• Deep understanding of distributed training, accelerator architectures, and collective communication