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Robot Learning Engineer (Reinforcement Learning / Imitation Learning)
Hamilton, ON · Canada
Full Time
AI team
You will develop learning-based systems that enhance autonomy, adaptability, and robot behavior across ROZOR robots, RL/IL models for navigation in complex spaces and refining behaviors for cleaning or delivery tasks in dynamic indoor settings.
Responsibilities
- Develop reinforcement / imitation learning algorithms for navigation, manipulation, and task execution.
- Build training pipelines in simulation for scalable robot learning.
- Create policies for obstacle avoidance and motion planning in dynamic environments.
- Design reward functions, curriculum strategies, and evaluation metrics.
- Analyze and reduce simulation-to-reality gaps.
- Collaborate with autonomy, perception, and embedded teams to integrate learned policies.
- Improve robustness and generalization of learned behaviors.
What you bring
- Bachelor's/Master's in Robotics, AI, Computer Science, or related field.
- Expertise in reinforcement learning, imitation learning, or decision-making algorithms.
- Proficiency in PyTorch, TensorFlow, and modern simulation frameworks.
- Experience with ROS / ROS 2.
- Strong understanding of robot kinematics, navigation, and control systems.
- Strong mathematical foundation in optimization, probability, and machine learning.
How to apply
Send your CV and a short note about your work.
Tell us why this role fits you and link any work like repos, papers, demos, or robots that shows what you build.