A day in the life and how youll make an impact
Design and train deep learning models for robot perception, including 3D scene understanding, vehicle pose, and occlusion handling.
Develop visuomotor and policy models for sensor positioning, navigation, and manipulation around vehicles.
Adapt and integrate existing inspection models onto the robotic platform.
Build sim-to-real pipelines and run experiments in simulation and on real hardware, iterating fast on failure modes.
Own the technical quality and reliability of the AI stack as it moves from prototype to production.
4+ years of industry experience in robotics, perception, or applied ML, with deep learning models shipped to production.
Strong background in at least one of: 3D vision (SLAM, depth estimation, point clouds, NeRF), robot learning (visuomotor policies, imitation, RL), or manipulation.
Hands-on experience training and deploying models in PyTorch or TensorFlow.
Experience with simulation tools (Isaac Sim, MuJoCo, Gazebo, or equivalents) and with running models on real robotic hardware.
Strong Python skills; familiarity with ROS or ROS 2, an advantage.
Comfortable in unexplored territory, independent, and strong at iterating on hardware in the loop.
M.Sc./Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related field, a strong advantage.


















