Staff AI Infrastructure Engineer

Luma AI

$230K — $360K *
Technical Services
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Deep expertise in Linux and distributed systems
  • Experience operating GPU/accelerator clusters in production
  • Strong fluency in Kubernetes and open-source infrastructure
  • Skilled in debugging across hardware, kernel, runtime, and orchestration
  • Understanding of systems behavior under contention and scale
  • Ability to write code and build automation
  • Proven judgment trusted by engineering peers during failures

Responsibilities

  • Architect and operate large, heterogeneous GPU environments
  • Improve utilization and performance for significant gains
  • Resolve failures across hardware, OS, and orchestration
  • Eliminate classes of instability in systems
  • Build systems that make heroics unnecessary
  • Define infrastructure evolution as cluster size and concurrency grow
  • Design resource management strategies for complex jobs
  • Ensure rapid scaling of inference platforms without reliability loss
  • Anticipate and redesign to prevent future failure modes
  • Hire and develop exceptional systems engineers

Benefits

  • Opportunities for professional development
  • Collaborative work environment
  • Influential role in defining AI infrastructure reliability
  • Impact on product scalability and research progression
  • Access to cutting-edge technologies and projects
Full Job Description
Where You Come In

Our Infrastructure Engineering team is a systems engineering group with company-level responsibility. At Luma, reliability engineers work directly with the researchers and products pushing the limits of multimodal intelligence.

We operate close to the metal:

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


But we are also responsible for something bigger:

Turning deep systems knowledge into repeatable, scalable reliability for the entire company. We are hiring a leader who will define that direction. You will be a technical authority, an organizational force multiplier, and a magnet for other great engineers.

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


Important: This role requires comfort operating close to upstream and close to the metal. If most of your experience has been inside highly abstracted internal platforms where others owned the underlying machinery, this is unlikely to be a match.

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

Most infrastructure roles optimize mature systems. This one helps define how reliability works for a new generation of AI infrastructure.

The decisions you make here will influence:

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


If you want to build the reliability foundations of a company operating at the technological frontier, we should talk.

Compensation

The base pay range for this role is $230,000 - $360,000 per year.

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