Member of Technical Staff - GPU Infrastructure Engineer

Liquid AI is a company spun out of MIT CSAIL that builds general-purpose AI systems. They are seeking a GPU Infrastructure Engineer to manage and improve the reliability and efficiency of GPU clusters that support training and research, ensuring that researchers can focus on model development without infrastructure delays.

Responsibilities:

• Own the reliability and operation of the GPU clusters used for training and research
• Debug issues across compute, storage, networking, schedulers, and distributed workloads
• Improve CPU, GPU, and storage utilization through better tooling and automation
• Onboard and migrate workloads across GPU providers and hardware platforms
• Build monitoring, validation, and platform abstractions that reduce operational work for researchers
• Contribute to the longer-term architecture of Liquid AI’s training infrastructure and GPU platform