Research Scientist – Controlled 3D Generation
Remote • Remote
Posted 4mo ago
Job Location
Remote
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Research Engineer
About the job
We are seeking a Research Scientist passionate about 3D generation, flow matching, and diffusion models. You will help advance the frontier of controllable 3D content creation by building models that generate consistent, editable, and physically grounded 3D assets and scenes. This role involves conducting cutting-edge research, designing and implementing scalable training pipelines, and developing techniques for conditioning and control. You will analyze model behavior, collaborate with cross-disciplinary teams to translate research into production-ready systems, and publish results at top-tier venues.
Responsibilities
- Conduct 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.
- Analyze model behavior through ablations, visualizations, and quantitative metrics.
- Collaborate with research, graphics, and infrastructure teams to translate research into production-ready systems.
- Publish results at top-tier venues and work with interns.
Requirements
- 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 optimization.
- Understanding of 3D representations (meshes, Gaussians, signed-distance fields, volumetric grids, implicit networks).
- Solid grasp of geometry processing, multi-view consistency, and differentiable rendering.
- Ability to scale experiments efficiently and communicate complex results clearly.