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Salary
$94k – $232k per year (Estimated)
Location
Remote/Hybrid (Toronto, Canada)
Employment
Full-Time
Overview
Company
Impact
Profile match
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.

As a Research Engineer in Neural Rendering, you will create the next generation of multi-sensor rendering systems for autonomous driving. You will collaborate with our team of world-renowned scientists and engineers to build innovative, practical, and scalable rendering and content creation solutions for self-driving. We value original, high-impact ideas and rigorous experimental validation.

You will…

- Be part of a team of multidisciplinary Research Scientists and Engineers working on building a best-in-class multi-sensor simulation stack.

- Use cutting edge techniques in reconstruction, neural rendering and generative AI to build large-scale, efficient digital twins from real-world camera, LiDAR, and RADAR data. You will work on shipping next-generation simulation software which mixes traditional real-time rendering with NeRF, 3D Gaussian Splatting, diffusion models, etc.

- Collaborate with Waabi’s autonomy and safety teams to improve the realism and diversity of Waabi World.

- Have the opportunity to make contributions to high-impact research papers submitted to top conferences or journals (CVPR, ECCV, ICCV, SIGGRAPH, NeurIPS, ICLR, ICRA, RA-L).

Qualifications:

- Shipping Production Software. You have experience in reading and developing production quality software, versus only creating prototypes and proofs of concept. You are comfortable working with large datasets for ML applications.

- Deep understanding of ML or neural rendering. You are familiar with the internals of modern machine learning (diffusion models, vision foundational models) or neural rendering (NeRF, 3DGS) systems beyond just application. You understand the limitations of current methods and the different trade-offs between paradigms.

- Cloud Machine Learning. Experience designing, launching, and debugging GPU machine learning jobs in the cloud (PyTorch, TensorFlow).

- Strong software engineering fundamentals. You write efficient and maintainable code in Python and PyTorch, as well as in at least one native systems language such as C++ or Rust.

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