Robotics AI Engineer

At UVeye, we’re on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the world’s first fully automated suite of vehicle inspection systems, with advanced AI at the core, spanning machine learning, GenAI, and computer vision across the automotive sector.

With close to $400M in funding and strategic partnerships with industry giants such as Amazon, General Motors, Volvo, and CarMax, UVeye stands at the forefront of automotive technological advancement. Our growing global team of over 300 employees is united around a culture of innovation, excellence, and teamwork as we build a safer automotive world.

We are looking for an experienced Robotics AI Engineer to build the AI core of UVeye’s robotics inspection platform. You will design and ship the perception and policy models that let a mobile, dexterous robot approach a vehicle, position sensors, and complete inspection tasks reliably in real-world environments.

A day in the life and how you’ll 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 UVeye’s 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.