Staff AI Infrastructure Engineer

About Luma AI

Where You Come In

• Kernels
• Containers
• Schedulers
• Networking
• Storage
• GPU behavior

What You’ll Own

Reliability of the Frontier

• 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

Scaling Training & Inference

• Define how infrastructure and workloads evolve as cluster size and concurrency grow
• Design scheduling, placement, and resource management approaches for increasingly complex jobs
• Work directly with research to build the systems required for new model capabilities
• Ensure inference platforms scale rapidly without sacrificing reliability or latency
• Anticipate where today’s abstractions will fail and redesign ahead of them

Building the Organization

• Hire and develop exceptional systems and reliability engineers
• Set the bar for technical depth, judgment, and production ownership
• Shape architecture early through strong partnerships with research and product
• Translate reliability constraints into long-term platform strategy

Who You Are

Required:

• 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

Leadership Expectations

• You raise reliability standards across the company
• You influence product and research architecture early
• You build strong partnerships, not ticket queues
• You attract and level up exceptional engineers
• You are curious how models use infrastructure, because improving systems expands what becomes possible

Why This Role Is Special

• How research progresses
• How products scale
• How customers trust us
• And how the engineering organization grows

Compensation

About Luma