Waabi’s autonomous-driving stack is powered by Waabi World, which delivers realistic, scalable, controllable, and efficient simulation. As a Research Engineer in the World Models team, 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…
- Design, implement, and scale state-of-the-art generative and predictive world-modeling systems:
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 closely with Research Scientists to translate cutting-edge model prototypes into robust, large-scale, distributed training and inference pipelines.
- Optimize model training and inference for efficiency, speed, and reliability on large-scale datasets.
- Build large scale data pipelines to build high quality datasets for training
- Ensure the quality, stability, and maintainability of the world model codebase and infrastructure.
- Stay on top of emerging advances in generative AI, distributed systems, and efficient model deployment in robotics.
Qualifications:
- Strong software engineering and implementation: You have very strong Python & PyTorch (or JAX) skills; strong software-engineering fundamentals, and extensive experience with distributed training and large-scale model deployment.
- Demonstrated technical impact: You have a Master's degree in Computer Vision, Machine Learning, Robotics, or a related field, or equivalent industry experience in model development and scaling.
- Expert domain knowledge: You have built and deployed generative or predictive models of the physical world, focusing on scale, efficiency, and robustness 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 in a fast-paced environment.
Bonus:
- Experience with infrastructure and tooling for large-scale ML training (e.g., cloud platforms, Kubeflow, Ray).
- Experience with efficient model serving and deployment (e.g., ONNX, TensorRT).
- Publications or research at top ML/CV/Robotics conference (e.g., CVPR, ECCV, NeurIPS)
Skills Required
- Master's degree in Computer Vision, Machine Learning, Robotics, or related field or equivalent industry experience
- Very strong Python skills
- Experience with PyTorch or JAX
- Strong software-engineering fundamentals
- Extensive experience with distributed training and large-scale model deployment
What We Do
Waabi, founded by AI pioneer and visionary Raquel Urtasun, is an AI company building the next generation of self-driving technology. With a world class team and an innovative approach that unleashes the power of AI to “drive” safely in the real world, Waabi is bringing the promise of self-driving closer to commercialization than ever before. Waabi is backed by best-in-class investors across the technology, logistics and the Canadian innovation ecosystem, including Khosla Ventures, Uber, 8VC, Radical Ventures, OMERS Ventures and BDC Capital’s Women in Technology Venture Fund. To learn more visit: waabi.ai Press: [email protected] Business: [email protected]
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