Research Scientist, Neural Reconstruction
Waabi
Waabi World depends on accurate, scalable, and efficient reconstruction of the 3D/4D physical world from real-world sensor data. As a Research Scientist in Neural Reconstruction, you will develop the next generation of neural scene-representation and reconstruction algorithms that transform sparse, noisy, and partially observed driving data into realistic and controllable digital worlds.
This role focuses on 3D/4D neural reconstruction and rendering, including 3DGS/NeRF, neural scene representation, and generalizable reconstruction models. Your work will directly power Waabi World’s ability to build high-fidelity scene assets, recover geometry and dynamics from sensor data, and support realistic simulation and rendering at scale.
You will…
- Conduct fundamental and applied research in neural reconstruction, including:
• 3DGS / NeRF
• Dynamic scene reconstruction
• Feed-forward reconstruction
• Multi-sensor scene representation learning
- Build scalable reconstruction and simulation systems for dynamic urban scenes, including vehicles, background, lighting, and long-range structure.
- Collaborate with simulation engineers to integrate models into large-scale, distributed training and rendering pipelines.
- Publish high-impact research at top conferences (CVPR, ECCV, ICCV, NeurIPS, ICLR, ICRA, SIGGRAPH).
- Mentor junior scientists and interns; foster a culture of scientific rigor and rapid experimentation.
- Stay current with emerging advances in neural rendering, 3D representation learning, differentiable rendering, and scalable reconstruction systems.
Qualifications:
- Demonstrated technical innovation: You have a Ph.D. in Computer Vision, Machine Learning, Robotics, or a related field or equivalent research experience pushing the boundaries of a technical field..
- Strong prototyping and implementation: You have expert-level Python & PyTorch (or JAX) skills; strong software-engineering fundamentals and experience with distributed training.
- Expert domain knowledge: You have built generative or predictive models of the physical world with scale and efficiency in mind for real-world applications
- Team player: You have worked in a close-knit team of researchers and engineers and have strong communication to deliver successful projects.
Bonus:
- Proven ability to translate research into production-quality code and measurable product impact.
- Demonstrated first-author publications in top-tier venues on topics such as:
• 3DGS / NeRF / neural rendering
• 3D / 4D reconstruction
• Generalizable reconstruction
• Geometry-aware or multi-sensor representation learning
- Experience working with camera, LiDAR, maps, and large-scale driving datasets.
- Strong background in graphics, geometry, rendering systems, or simulation.
