Research Scientist - World Model

You'll turn Luma's industry-leading generative video models into world models: interactive, controllable, physically faithful, and useful as a substrate for embodied reasoning. This is the role at the center of the thesis.

You'll invent next-generation world-model architectures and the controllability that lets an agent step into a generated world, and own the metrics that define success. It fits a researcher with deep generative-modeling or model-based-RL expertise who has trained models to the limits of a multi-node cluster. If you want a narrow, well-scoped research problem, this is broader and more open-ended than that.

What You'll Own

• Invent next-generation world-model architectures (diffusion, transformer, autoregressive, or hybrid), focused on controllability and physical consistency.
• Develop controllability mechanisms — action conditioning, view conditioning, long-horizon rollouts — that let an agent step into the world.
• Define and own the metrics: physical fidelity, long-horizon coherence, action-following, and downstream usefulness for policy training.