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Huawei Canada

Chief Scientist - Physical AI

Reposted 2 Months Ago
Be an Early Applicant
In-Office
Markham, ON, CAN
Expert/Leader
In-Office
Markham, ON, CAN
Expert/Leader
The Chief Scientist will develop advanced Physical AI approaches, oversee experiments, integrate data and models, and lead impactful research in AI.
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Huawei Canada has an immediate permanent opening for a Chief Scientist.

About the team:

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.  

About the job:

  • 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.

About the ideal candidate:

  • 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.

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

  • Experience working with large-scale datasets, sensor data, and advanced architectures such as transformers or diffusion models.

Additional Information:

Huawei Canada is committed to a fair, inclusive, and accessible recruitment process. If you require accommodation during any stage of the hiring process, please let us know, and we will work with you to meet your needs.

All applications for this position are reviewed directly by our hiring team, we do not use artificial intelligence tools to screen or select candidates.

Huawei aims to support a French-speaking work environment for its employees in Quebec. We have taken steps to avoid requiring a language other than French for this position. However, proficiency in English is essential for this role for the following reasons:

The person will be required to communicate regularly with colleagues located outside Quebec, where English is the primary language used for communication between offices. In addition, the nature of the tasks related to this position, which falls within a highly specialized field of artificial intelligence, also requires knowledge of English.

Huawei Canada Markham, Ontario, CAN Office

19 Allstate Pky, Markham, Ontario, Canada, L3R 5A4

Huawei Canada Toronto, Ontario, CAN Office

Toronto, Canada

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