Lead AI Infrastructure Engineer: GPU Clusters & Reliability

Luma AI; San Francisco (CA); On-site; USD 300,000 - 420,000; Full time

Job summary

Luma AI in San Francisco is seeking a leader to define reliability for a frontier AI infrastructure. You will architect and operate large GPU environments, pushing the limits of training and inference while partnering with research and product to scale systems and improve availability.

The role demands deep Linux/distributed systems expertise, strong Kubernetes mastery, and a track record of delivering scalable, production‑grade infrastructure.

Qualifications

• Deep expertise in Linux and distributed systems.
• Experience operating GPU/accelerator clusters in real production environments.
• Strong fluency in Kubernetes and modern open‑source infrastructure.
• Comfortable debugging across hardware → kernel → runtime → orchestration.
• You understand how systems behave under contention and at scale.
• You write code and build automation.
• You think in bottlenecks, failure modes, and tradeoffs.
• Engineers trust your judgment, especially when things break.

Responsibilities

• Architect and operate large, heterogeneous GPU environments under extreme demand.
• Improve utilization and performance where small gains materially change company outcomes.
• Resolve failures that span hardware, OS, runtimes, and orchestration.
• Eliminate entire classes of instability.
• Build mechanisms that make heroics unnecessary.

Skills

Linux

Distributed systems

Kubernetes

GPU clusters

Open‑source infra

Debugging hardware to orchestration

Performance & bottlenecks

Automation / SRE scripting

Leadership / mentoring

Tools

Kubernetes

Linux

Job description

Luma AI in San Francisco is seeking a leader to define reliability for a frontier AI infrastructure. You will architect and operate large GPU environments, pushing the limits of training and inference while partnering with research and product to scale systems and improve availability.

The role demands deep Linux/distributed systems expertise, strong Kubernetes mastery, and a track record of delivering scalable, production‑grade infrastructure.