PhD in Computer Science, Robotics, or 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 prestigious venues (NeurIPS, ICML, CVPR, etc.).
Proficient in Python and deep learning frameworks (PyTorch, TensorFlow).
Hands-on experience with robotics systems, including planning and control; real robot or ROS experience is a plus.
Experience with large-scale datasets, sensor data, transformer architectures, or diffusion models is beneficial.
Familiarity with reinforcement learning and/or imitation learning is an asset.
Responsibilities
Collaborate with researchers and engineers on Embodied AI and Spatial AI challenges.
Develop cutting-edge approaches for Physical AI applications such as robotic foundation models and reasoning.
Translate research models into efficient, production-ready code and iterate through rapid experimentation.
Design and execute experiments across simulation and real-world robotic platforms, focusing on data collection and performance analysis.
Work collaboratively with teams to integrate data, models, and real-world robotic performance.
Contribute to impactful research outputs including patents and high-profile publications.
Benefits
Opportunity to work on pioneering AI and robotics technologies.
Exposure to interdisciplinary collaboration in research and engineering.
Support for patent publication and research dissemination.
Hands-on experience with advanced robotics and AI systems.
Direct engagement with top researchers in the field.
Full Job Description
Huawei Canada has an immediate permanent opening for a Senior Researcher.
About the job:
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.
The total target annual compensation for this position ranges from $127,000 to $225,000 depending on education, experience, and demonstrated expertise.
About the ideal candidate:
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 would be highly desirable.
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.
All applications for this position are reviewed directly by our hiring team, we do not use artificial intelligence tools to screen or select candidates.
