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

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

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)

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)

The US yearly salary range for this role is: $155,000 - $269,000 USD in addition to competitive perks & benefits. Waabi US Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:

- Competitive compensation and equity awards.

- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).

- Unlimited Vacation.

- Flexible hours and Work from Home support.

- Daily drinks, snacks and catered meals (when in office).

- Regularly scheduled team building activities and social events both on-site, off-site & virtually.

- As we grow, this list continues to evolve!

Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!

Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.

Research Engineer, World Models