# Research Scientist - World Model at Luma

Research Scientist - World Model at Luma in Redwood City, CA. Hybrid, full-time. Posted July 24, 2026.

- Company: Luma
- Location: Redwood City, CA
- Workplace: Hybrid
- Job type: Full-time
- Posted: 2026-07-24
- Apply: https://jobs.ashbyhq.com/lumaai/ed5b169b-7aef-4f84-993b-42a5aabd1bd4/application
- Source: https://jobmagic.ai/jobs/research-scientist-world-model-luma-0zd8fd

## Description

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.

- Run scaling studies that show where compute, data, and architecture pay off.

- Publish at the frontier and contribute to the open-source release that is the long-term deliverable.

**First 90 Days**
*One way the first 90 could unfold.*

- **Days 1–30 — Immerse & Diagnose:** Get deep on the current video models and where they fall short as world models.

- **Days 30–60 — Ship & Validate:** Prototype a controllability mechanism or architecture change and measure it against physical-fidelity and action-following metrics.

- **Days 60–90 — Scale & Systemize:** Run scaling studies and push the most promising direction toward the open release.

**What You Bring**

- PhD or equivalent research record in ML, computer vision, robotics, or a related field.

- Deep expertise in at least one of: large-scale generative modeling (video/3D/world), self-supervised representation learning, or model-based RL.

- Strong PyTorch and large-scale training experience, to the limits of a multi-node cluster.

- A research record the field knows (top-venue publications and/or widely used open releases).

**Nice to Have**

- Prior work on world models, model-based RL, generative video, neural simulation, or 4D scene representations.

- Experience using generative models for downstream embodied tasks (planning, control, evaluation).

- Enthusiasm for open-sourcing frontier models.

*About Luma: Luma's mission is to build unified general intelligence that can generate, understand, and operate in the physical world. We believe multimodality is critical for intelligence — the next step beyond language models comes from vision. Luma is an equal opportunity employer.*