Robot Learning Engineer
Core
Entry-level research and engineering role applying state-of-the-art machine learning to automate factory tasks like surface finishing, welding, and coating in a real robotic work cell.
Role type
Entry-level robot learning engineer (research & deployment)
Builds
Production ML models for robot perception, task understanding, and control deployed on real hardware
Domain
Industrial robotics + AI/ML for physical systems
Deliverable
production ML models
Required skills
Python, PyTorch or TensorFlow, robot learning (robotics, computer vision, ML for physical systems), rigorous experimental design, sim-to-real transfer concepts
Preferred skills
ROS or ROS 2, physics simulators (Isaac Sim, PyBullet, MuJoCo), 3D perception/point clouds/depth estimation, research publications or open-source contributions
Technologies
ROS 2, PyTorch, TensorFlow, Isaac Sim, PyBullet, MuJoCo
Responsibilities
Research and evaluate ML models for robot perception and task understanding; Apply computer vision and deep learning to sensor data (cameras, force/torque, depth); Experiment with reinforcement learning and imitation learning for robot control; Integrate AI models into a ROS 2 robotics software stack; Run rigorous experiments, measure results, and iterate quickly; Bridge the gap between research prototypes and real-world factory deployment
Seniority
Entry-level (0-3 years experience, new graduates welcome)
