Waabi is a Toronto-based Physical AI company developing a single, verifiable AI brain and neural simulator for autonomous trucks and robotaxis.
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 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.