Robot Perception/ML Engineer (f/m/d) Autonomous Mobile Robots

In this role you will design and improve perception models for autonomous mobile robots, focusing on object detection, obstacle classification, and free-space estimation. You will drive a data-centric ML approach by scaling labeling, leveraging fleet data, and bridging sim2real through synthetic data and simulation-based evaluation. You will own model performance with benchmarks and metrics, and ensure reliable ROS-based deployment on real vehicles. Collaboration with navigation, controls, and fleet software teams will shape robust perception capabilities for autonomous operation.

• holiday
• Wellpass
• health care
• compensation packages
• free lunch
• hybrid work model

• Develop and improve perception models (object detection, obstacle classification, free-space estimation) for autonomous robots
• Scale automated labeling, leverage fleet data, and close the sim2real gap via synthetic data and simulation-based evaluation
• Define benchmarks, track key metrics, and iteratively improve real-world and benchmark results
• Deploy and validate perception models within a ROS-based robot software stack on real vehicles
• Collaborate with navigation, controls, and fleet software teams to enable robust autonomous perception

• 2–5 years of hands-on experience in robotics perception, computer vision, or machine learning
• Strong Python skills; C++ is a plus
• Hands-on experience training and evaluating neural networks (PyTorch or similar) with a data-centric approach
• Experience with synthetic data, simulation for ML, auto-labeling, active learning, or domain adaptation
• Rigorous model evaluation and real-world performance measurement
• Familiarity with ROS and Linux-based development environments
• Pragmatic engineering mindset focused on shipping, measuring, and iterating

• collaboration
• data-driven mindset
• hands-on teamwork
• Python
• C++ (plus)
• PyTorch (or similar)