Research Scientist, World Models

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’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 Models that can reason about complex, dynamic 4D environments.

This role focuses on large-scale world models for temporal reasoning and generation, including video models, multimodal generative models, LLM/VLM/VLA models, and predictive models of traffic participants and scenes. Your work will directly power Waabi World’s ability to model future evolution, synthesize realistic safety-critical scenarios, and provide rich generative priors for downstream planning, testing, and training.

You will…

Conduct fundamental and applied research in generative and predictive world-modeling

Video generation and prediction.

Latent diffusion / autoregressive / flow-matching models.

Multimodal foundation models for driving scenes.

LLM / VLM / VLA methods for scene understanding, reasoning, and control.

Generative scenario modeling and controllable simulation.

Model distillation.

Collaborate with 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:

D emonstrated 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, diffusion, flow-matching, or foundation models for autonomy.