Luma AI is the creative AI platform for video generation and image creation. Powered by the world's leading video generation models, Ray and Uni, and creative agents handling end-to-end workflows. Trusted by leading agencies and brands. Try it free. Backed by General Catalyst, a16z and CRV.
About the role
You'll build and train large-scale multimodal agentic models — systems that reason, plan, code, and call tools to do complex, multi-step work over pixels. This is core research shaping how users interact with what Luma's models can do.
What they're looking for
- Strong foundation in machine learning, foundation models, and agentic systems
- Deep understanding of agentic systems and LLM/VLM reasoning, coding models, and tool calling
- Hands-on PyTorch and large-scale training (distributed, mixed precision, large datasets)
More about this role
You'll build and train large-scale multimodal agentic models — systems that reason, plan, code, and call tools to do complex, multi-step work over pixels. This is core research shaping how users interact with what Luma's models can do.
It's a multi-stack research role across modeling, data, systems, and evaluation, on novel problems with no existing playbook, treating science and engineering as equally important. It fits someone grounded in foundation models and agentic systems who's trained models at real scale. If you want to work in only one layer of the stack, this deliberately spans several.
Architect large-scale multimodal agentic models that use reasoning, planning, coding, and tool calling for complex, multi-step work.
Design, build, and run robust data pipelines to construct, enrich, and filter massive pixel datasets, and formulate new tasks.
Train large-scale multimodal models on massive datasets and GPU clusters.
Define and build novel evaluation frameworks to measure multimodal agents.
One way the first 90 could unfold.
Days 1–30 — Immerse & Diagnose: Learn the current models, agentic approaches, and where evaluation and data are weakest.
Days 30–60 — Ship & Validate:...
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