Researcher - Physical AI

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 Next Generation Foundation Model, Agentic Models, Physical AI and Reinforcement Learning.

• Work closely with a team of researchers and engineers to tackle real-world challenges in Embodied AI and Spatial AI, bridging research and deployment.

• Developing state-of-the-art approaches for Physical AI research and applications. Directions include, but not limited to, robotic foundation models, world models, multimodal representation learning, reasoning and planning, imitation learning and reinforcement learning and low-level control.

• Translate problem formulations and model designs into efficient, production-ready code, and iterate rapidly through rapid experimentation.

• Design and run experiments across both simulation and real-world robotic platforms, including data collection, evaluation, and performance analysis.

• Collaborate across research, infrastructure, and robotics systems to close the loop between data, models, and real-world performance.

• Contribute to high-impact research outputs, including patents and publications in top-tier AI and robotics venues.

• PhD in Computer Science, Robotics, or a related field (or Master’s with equivalent experience).

• Strong background in generative AI and sequence modeling, particularly in vision-language or multimodal systems.

• Proven research track record with first-author publications in top-tier venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, or ICRA.

• Proven research record in AI by having at least one paper as the first author in top tier venues, such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICRA.

• Proficient in Python and experienced with modern deep learning frameworks (e.g., PyTorch, TensorFlow).

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

• Experience working with large-scale datasets, sensor data, transformer-based architectures, or diffusion models is an asset.

• Familiarity with reinforcement learning and/or imitation learning methods is an asset.

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.