Member of Technical Staff, Infrastructure

Responsibilities

• Design and improve scheduling and resource allocation for inference and training coexistence on shared GPU clusters
• Build, operate, and scale GPU infrastructure across clusters of thousands of GPUs
• Own GPU utilization and cost as first-class metrics
• Build automated tooling and observability that reduces friction for the AI team
• Participate in on-call rotation and drive reliability improvements
• Serve as the primary point of contact for GPU providers, managing relationships and coordinating infrastructure needs
• Set scheduling policy and drive architecture decisions for compute and storage systems over time

Requirements

• Linux-native systems expertise with ability to debug at the kernel level
• Deep understanding of networking and storage stacks
• Experience operating and scaling GPU infrastructure (hundreds to thousands of GPUs)
• Kubernetes, Slurm, and distributed storage systems operation
• Track record of running critical infrastructure reliably with monitoring, incident response, and automation
• Sufficient understanding of training and inference workloads to collaborate with researchers

Preferred Qualifications

• Experience in resource-constrained environments where allocation, scheduling, and prioritization of scarce resources was the core problem (e.g., HPC, trading, large-scale ML platforms)

Benefits

• Competitive salary and equity
• Private health coverage
• Pension contribution (UK, Canada, US)
• Fully-distributed, async-first culture
• Hardware setup of your choice
• Stipends for phone, internet, and meals

About the Company

Moonvalley AI builds world models for media and entertainment, training and deploying AI systems at scale across thousands of GPUs.