About
Luma Research Lab was founded on a simple observation: GPU scarcity is the primary bottleneck on AI progress, and it's largely artificial. Vast amounts of compute — spot fleets, prior-generation accelerators, idle Trainium nodes — go underutilized because the software to federate and use them reliably doesn't exist yet. We're building it.
Mission
GPU scarcity is the defining bottleneck of the AI era — yet enormous amounts of compute sit underutilized: spot fleets that go unallocated, prior-generation accelerators that cost more to manage than they earn, Trainium nodes that require months of porting work before a single model trains. The scarcity is real, but much of it is a software problem.
Luma Research Lab builds the cloud stack that closes this gap. Our sealed compiler lets any Hugging Face model run on AWS Trainium with zero porting. Our orchestration layer federates heterogeneous hardware — H100s, A100s, TPUs, spot instances — into one logical training cluster. Our failover system turns volatile spot capacity into reliable, on-demand-equivalent infrastructure.
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Values
GPU scarcity is largely a software problem. We solve it with better orchestration, compilation, and failover — not by waiting for more chips to arrive.
We protect our research and our partners' investments. Proprietary techniques, model weights, and training recipes are shared selectively through structured agreements — never by default.
No customer should be locked to one cloud or one chip vendor. We build the portability layer so they never have to be.
If a model runs on one accelerator, it should run on all of them — without the customer touching a line of code. That's the bar we hold ourselves to.
Advisors
We're grateful for the guidance of researchers and practitioners across academia and industry.
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Careers
We're a small team. Every hire matters. We look for intellectual rigor, a bias toward openness, and genuine excitement about hard problems at the frontier of AI.
We'll post positions here as we grow. In the meantime, feel free to reach out at the email below.
Contact
We're open to research collaborations, compute partnerships, and press inquiries.
Joint projects, dataset sharing, benchmark contributions.
[email protected]