Website Stability AI
About the Role
We’re seeking a Research Scientist passionate about 3D generation, flow matching, and diffusion models. You’ll help advance the frontier of controllable 3D content creation — building models that generate consistent, editable, and physically grounded 3D assets and scenes.
What You’ll Do
- Conduct cutting-edge research on flow-matching, diffusion, and score-based methods for 3D generation and reconstruction.
- Design and implement scalable training pipelines for controllable 3D generation (meshes, Gaussians, NeRFs, voxels, implicit fields).
- Develop techniques for conditioning and control (text, sketch, pose, camera, physics) and multi-view consistency.
- Analyse model behaviour through ablations, visualisations, and quantitative metrics.
- Collaborate with cross-disciplinary research, graphics, and infrastructure teams to translate research into production-ready systems.
- Publish results at top-tier venues and work with interns.
What You Bring
- PhD (or equivalent experience) in Machine Learning, Computer Vision, or Computer Graphics.
- Published work on diffusion, flow-matching, or score-based generative models (2D or 3D).
- Strong engineering and problem-solving abilities: experience with PyTorch, JAX, or CUDA-level optimisation.
- Understanding of 3D representations (meshes, Gaussians, signed-distance fields, volumetric grids, implicit networks).
- Solid grasp of geometry processing, multi-view consistency, and differentiable rendering.
Bonus / Preferred
- Experience generating coherent 3D scenes with multiple interacting objects, lighting, and spatial layout.
- Familiarity with scene-level control (object placement, camera path, simulation, or text-to-scene composition).
- Knowledge of video-to-3D, image-to-scene, or 4D temporal generation.
- Background in physically-based rendering, simulation, or world-model architectures.
To apply for this job please visit job-boards.greenhouse.io.
