Senior Robotic Learning Engineer (m/f/d)

Skip to main contentEnglishEnglishBack to all jobsSenior Robotic Learning Engineer (m/f/d)Germany, Munich (HQ)Full-timePermanent employeeApply for this jobAbout the roleThe AI Research Division of Agile Robots is looking for a Senior Robotic Learning Engineer (m/f/d), who will architect the full pipeline that turns raw robot and human data into deployed foundation models, from collection through post-training to on-robot deployment.Your ResponsibilitiesSystem Architecture: Own how collection, generation, augmentation, annotation, valuation, and evaluation fit together as one coherent data-to-model pipeline, and prioritize engineering investment where it most improves model performance.Model Evaluation & Deployment: Integrate post-training and evaluation frameworks, in simulation and on real hardware, and own the path to reliable, automatic deployment on robotic platforms.Data Valuation & Curation: Develop methods and metrics to assess data quality and value — diversity, coverage, redundancy, task relevance — and use them to guide what gets collected, kept, or discarded.Data Generation: Build synthetic and simulation-based data generation pipelines, including real-to-sim-to-real transfer, procedural task and scene generation, and generative models, to scale training data beyond physical collection alone.Data Collection: Design scalable systems for collecting both robot-generated data (teleoperation, autonomous rollouts, scripted policies) and human data (egocentric video, demonstrations) to train imitation learning and VLA models.Cross-Team Collaboration: Partner with research scientists, robotics engineers, and infrastructure teams to translate model and research needs into production data and evaluation systems.Essential SkillsBackground: Master's degree or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related field, or an equivalent combination of formal training and professional experience.Professional Experience: 5+ years in robotics, autonomous driving, machine learning, or data engineering, with demonstrated ownership of systems spanning multiple pipeline stages, not a single component.Robot Learning: Hands-on experience with imitation learning, Vision-Language-Action models, robot foundation models, reinforcement learning, or other learning-based approaches to robotics.Programming: Software engineering proficiency in Python sufficient to build production-grade, reliable systems rather than research prototypes; familiarity with C++ is a plus.Systems-Level Thinking: Ability to reason about how a decision at one pipeline stage — what data is collected — affects outcomes at another, such as model performance or evaluation results, and to design across those boundaries.Beneficial SkillsSimulation: Experience with simulation platforms such as Isaac Sim or MuJoCo for synthetic data generation and sim-to-real transfer.Data Valuation Techniques: Familiarity with active learning, coreset selection, influence functions, or other methods for quantifying training data value.Human Data Collection: Experience with egocentric data collection, AR/VR devices, hand tracking, or teleoperation frameworks for embodied AI.Data Systems: Experience designing and operating large-scale data pipelines — collection, storage, processing, labeling — for machine learning training.Deployment & MLOps: Experience with model serving, edge or real-time inference, or cloud-based deployment infrastructure.What we offerDynamic high-tech company combined with financial soundness and world class investors.Join an interdisciplinary, international team with 60+ different nationalities in a collaborative work environment.Lots of development opportunities in the context of our continued growth.Challenging tasks and impactful projects alongside experts that enable professional and personal growth.Corporate Benefits Program that covers health, mobility and learning with 100 € net per month.Modern office facilites with a rooftop...