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Salary
$94k – $233k per year (Estimated)
Location
Remote/Hybrid (Toronto, Canada)
Employment
Full-Time
Overview
Company
Impact
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Waabi is an artificial intelligence and autonomous vehicle technology company headquartered in Toronto, Canada, founded in 2021. The company develops an end-to-end artificial intelligence software platform, known as the Waabi Driver, and a simulation environment called Waabi World to power autonomous trucks and robotaxis. It operates primarily in the North American logistics and transportation sectors through strategic partnerships with industry leaders such as Volvo, Uber Freight, and NVIDIA.

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.

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