Robotics AI Engineer (Deep Learning for Autonomy)
Summary
Design and deploy deep-learning models for autonomous robot navigation, including obstacle prediction, semantic mapping, and behavior forecasting.
Robotics AI Engineer (Deep Learning for Autonomy)
Hamilton, ON · Canada Full Time AI team
You will design, train, and deploy neural models that power high-level autonomy behaviors in ROZOR robots, obstacle prediction, semantic mapping, scene understanding, behavior forecasting, and learning-based navigation.
Responsibilities
- Develop deep learning for dynamic obstacle detection and motion prediction.
- Work on behavior forecasting in crowded environments.
- Handle semantic mapping and spatial understanding.
- Create learning-based navigation and path optimization.
- Process multi-modal data: RGB, LiDAR, depth, IMU, maps, and trajectories.
- Build training and validation pipelines.
- Integrate models into ROS 2-based autonomy stacks.
- Collaborate across planning, perception, and embedded teams.
- Conduct field testing and failure analysis.
- Support dataset generation and ML operations.
What you bring
- Bachelor's/Master's in AI, Robotics, Computer Science, or related field.
- Deep learning, computer vision, or reinforcement learning expertise.
- PyTorch or TensorFlow proficiency.
- Experience with time-series, trajectory data, or sequential prediction models.
- Robot navigation, SLAM, mapping knowledge.
- Detection, tracking, segmentation, or prediction training experience.
- Strong debugging and analytical abilities.