Waabi, founded by AI pioneer and visionary Raquel Urtasun, is an AI company building the next generation of self-driving technology. With a world class team and an innovative approach that unleashes the power of AI to “drive” safely in the real world, Waabi is bringing the promise of self-driving closer to commercialization than ever before. Waabi is backed by best-in-class investors across the technology, logistics and the Canadian innovation ecosystem.
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’s autonomous-driving stack is powered by Waabi World, which aims to deliver realistic, scalable, controllable, and efficient simulation. As a Research Scientist in World Models, you will develop algorithms and productionize the next generation of World Simulation models that can reason about complex, dynamic 4D environments with minimal supervision. Your work will directly power Waabi World’s ability to comprehend the 4D physical world, simulate traffic participants and generate realistic safety-critical scenarios at scale.
You will…
- Conduct fundamental and applied research in generative and predictive world-modeling (e.g., latent diffusion, video generation models, 3D Gaussian splatting, NeRF) on multi-sensor multi-modal data of driving scenes.
- 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 on top of emerging advances in generative AI, differentiable rendering, knowledge distillation/compression, and robotics.
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 publications (first-author) in top-tier venues on topics such as world models, generative simulation, video prediction, NeRF/3DGS, diffusion, flow-matching, or foundation models for autonomy.
