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.
