Waabi is hiring a Research Scientist in Toronto!
Waabi is hiring a Research Scientist into its World Models team in Toronto, working on the simulation engine that underpins the company's autonomous driving stack. The position sits at the intersection of fundamental and applied research: the successful candidate will design and productionize generative and predictive models capable of reasoning about complex, dynamic 4D environments. Output from this work feeds directly into Waabi World, giving the simulator the ability to forecast how scenes evolve, manufacture realistic safety-critical scenarios, and supply generative priors used downstream for planning, testing, and model training. The role blends deep research with engineering delivery, since models must ultimately run inside large-scale distributed training and rendering pipelines. It also carries a visible publication mandate and a mentoring component, making it a good fit for a PhD-level researcher who wants academic-calibre work with a commercial product attached to it.
Key responsibilities
- Pursue fundamental and applied research on generative and predictive world models, spanning video generation and prediction, latent diffusion, autoregressive and flow-matching approaches, multimodal foundation models for driving scenes, and LLM/VLM/VLA methods for scene understanding, reasoning, and control.
- Build generative scenario modeling and controllable simulation capabilities, including predictive models of traffic participants and scene evolution.
- Work with engineering teams to integrate research models into large-scale, distributed training and rendering infrastructure.
- Apply model distillation and compression techniques to keep models efficient at scale.
- Publish high-impact results at venues such as CVPR, ECCV, ICCV, NeurIPS, ICLR, ICRA, and SIGGRAPH.
- Mentor junior scientists and interns while promoting scientific rigor and fast experimentation.
- Track emerging work in generative AI, differentiable rendering, distillation, and robotics.
Key requirements
- PhD in Computer Vision, Machine Learning, Robotics, or a related area, or comparable research experience pushing a technical field forward.
- Expert-level Python plus PyTorch or JAX, with strong software engineering fundamentals and hands-on distributed training experience.
- Demonstrated experience building generative or predictive models of the physical world with scale and efficiency in mind for real-world use.
- Comfort working within a close-knit team of researchers and engineers, with strong communication skills.
- Assets: a track record of turning research into production-quality code with measurable impact, and first-author publications on world models, generative simulation, video prediction, diffusion, flow-matching, or foundation models for autonomy.
- Seniority: Senior individual contributor (PhD-level research role with mentoring duties)
- Work mode: Not specified; role based in Toronto
- Key skills: Python, PyTorch, JAX, distributed training, world models, video generation, diffusion models, flow matching, autoregressive models, multimodal foundation models, LLM/VLM/VLA, computer vision, generative simulation, model distillation, differentiable rendering
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