About Luma AI

A new class of intelligence is emerging, systems that understand and generate the world across video, images, audio, and language.

Building multimodal AGI is not just a modeling challenge. It is an infrastructure challenge at the edge of what hardware, software, and organizations can support.

At Luma, we operate rapidly scaling 10k+ GPU fleets, pushing utilization, throughput, and reliability hard enough that yesterday’s solutions break regularly. Researchers depend on this infrastructure to move the frontier forward. Customers depend on it to power real creative work.

Many companies run accelerators. Very few sit directly next to the teams inventing the models that redefine what those accelerators must do.

At Luma, improvements to scheduling, efficiency, and reliability immediately translate into faster research iteration and entirely new product capabilities.

We are still early. The playbook is still being written. A single exceptional engineer can reshape how the company operates.

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.

About Luma

Luma’s mission is to build unified general intelligence that can generate, understand, and operate in the physical world.

We believe that multimodality is critical for intelligence. To go beyond language models and build more aware, capable and useful systems, the next step function change will come from vision. So, we are working on training and scaling up multimodal foundation models for systems that can see and understand, show and explain, and eventually interact with our world to effect change.

Lead Infrastructure and Reliability Engineer (Systems & Scale)