Chief Scientist - Physical AI

Huawei Technologies Canada Co., Ltd.•Montreal, QC

52d

About The Position

Huawei Canada has an immediate permanent opening for a Chief Scientist. Founded in 2012, the Noah’s Ark lab has evolved into a prominent research organization with notable achievements in academia and industry. The lab’s mission focuses on advancing artificial intelligence and related fields to benefit the company and society. Driven by impactful, long-term projects, the aim is to enhance state-of-the-art research while integrating innovations into the company's products and services, including LLMs, RL, NLP, computer vision, AI theory, and Autonomous driving. The role involves working at the forefront of Embodied AI and Spatial AI, collaborating with researchers and engineers to solve real-world challenges and bridge cutting-edge research with scalable deployment. The Chief Scientist will develop state-of-the-art approaches in Physical AI, including robotic foundation models, world models, multimodal representation learning, reasoning and planning, as well as imitation and reinforcement learning with integrated low-level control. They will translate advanced problem formulations and model designs into efficient, production-grade systems, enabling rapid iteration through large-scale experimentation. The position requires designing and executing experiments across both simulation and real-world robotic platforms, covering data collection, evaluation, and performance analysis. Driving closed-loop learning by integrating data, models, and real-world feedback to continuously improve system robustness and adaptability is also a key responsibility. Collaboration across research, infrastructure, and robotics systems is essential to ensure end-to-end system coherence and scalability. The role also involves contributing to and leading high-impact research outputs, including patents and publications in top-tier venues.

Requirements

PhD in Computer Science, Robotics, AI, or a related field (or Master’s with equivalent research and industry experience).
Strong foundation in generative AI and sequence modeling, particularly in vision-language or multimodal learning systems.
Proven research track record with first-author publications in top-tier conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, or ICRA.
Solid expertise in modern deep learning frameworks (e.g., PyTorch, TensorFlow) and strong proficiency in Python.
Experience working with large-scale datasets, sensor data, and advanced architectures such as transformers or diffusion models.

Nice To Haves

Hands-on experience with robotics systems, including decision-making, planning, and control; experience with real-world robots or ROS is an asset.

Responsibilities

Work at the forefront of Embodied AI and Spatial AI, collaborating with researchers and engineers to solve real-world challenges and bridge cutting-edge research with scalable deployment.
Develop state-of-the-art approaches in Physical AI, including robotic foundation models, world models, multimodal representation learning, reasoning and planning, as well as imitation and reinforcement learning with integrated low-level control.
Translate advanced problem formulations and model designs into efficient, production-grade systems, enabling rapid iteration through large-scale experimentation.
Design and execute experiments across both simulation and real-world robotic platforms, covering data collection, evaluation, and performance analysis.
Drive closed-loop learning by integrating data, models, and real-world feedback to continuously improve system robustness and adaptability.
Collaborate cross-functionally across research, infrastructure, and robotics systems to ensure end-to-end system coherence and scalability.
Contribute to and lead high-impact research outputs, including patents and publications in top-tier venues such as NeurIPS, ICML, ICLR, CVPR, and ICRA.