Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech. With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai 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.