Machine Learning Engineer – Robot Learning (m/f/d)

Your MissionAs a Machine Learning Engineer – Robot Learning, you will help develop, evaluate, and deploy learning-based methods for real-world robotic manipulation. You will work at the intersection of machine learning, robotics, and systems engineering, adapting state-of-the-art research into robust, scalable capabilities that run on real hardware.You will collaborate closely with robotics, autonomy, perception, simulation, and software teams, and you will own ML workflows from model design to deployment and testing on real robots.Your ResponsibilitiesResearch, evaluate, and benchmark state-of-the-art robot learning methods (VLA models, diffusion policies, RL, imitation learning, visuomotor models)Adapt academic models for practical, real-world deployment on RobCo’s modular robotsTrain and fine-tune ML models using RobCo datasets and simulation dataIntegrate learned policies with perception, control, and robot runtime systemsBuild scalable training, evaluation, and data pipelines in collaboration with infrastructure teamsDefine clear performance metrics and build automated evaluation procedures in simulation and on real hardwareAnalyze model performance, identify regressions, and drive improvementsCollaborate with robotics and autonomy engineers to ensure safety, reliability, and real-time performanceParticipate in research planning and contribute to technical decisions across the robot learning stackShare knowledge, support junior team members, and help shape internal ML best practicesYour ProfileDegree in Machine Learning, Robotics, Computer Science, Mathematics, Engineering, or a related field (Master’s degree necessary)Hands‑on experience with robot learning, imitation learning, reinforcement learning, or deep learningStrong coding skills in Python and experience with PyTorch or JAXExperience training or evaluating ML models (university projects, internships, research labs, industry experience all count)Familiarity with robotics concepts or experience deploying ML on real systems (internship or lab experience is sufficient)Ability to design experiments, analyze model behavior, and communicate insights clearlyStrong problem‑solving mindset and eagerness to work on real robotsBonus: familiarity with ROS 2, scalable training tools (Ray, Anyscale), or robotic datasetsWhy us?Shape the robot learning capabilities of a next‑generation modular robotics platformWork with real hardware, simulation tools, rich datasets, and scalable ML infrastructureResearch‑focused culture with direct real‑world deploymentHigh ownership, autonomy, and strong technical growth opportunitiesHybrid work model, flexible hours, and cutting‑edge equipment #J-18808-Ljbffr