Lead Infrastructure and Reliability Engineer (Systems & Scale)

Luma AI is a pioneering company focused on building multimodal AGI systems that understand and generate content across various media. They are seeking a Lead Infrastructure and Reliability Engineer to architect and operate large GPU environments, improve system reliability, and build a strong engineering organization. This role is critical in defining the reliability standards for their cutting-edge AI infrastructure.

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
• 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
• 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

Requirements:

• 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