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System 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 Skills - Background: 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 Skills - Simulation: 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.

Das wird geboten

- A dynamic 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 as we continue to grow. - Challenging tasks and impactful projects alongside experts that enable professional and personal growth. - Corporate

Über das Unternehmen

Agile Robots is a leading provider of AI-powered robotics solutions. By combining artificial intelligence and robotics, the company makes industries smarter, more flexible, and more efficient. Founded in Munich in 2018 by renowned robotics researchers from the German Aerospace Center (DLR), Agile Robots has experienced rapid global growth.

Today, more than 3,500 highly skilled robotics and AI enthusiasts are employed worldwide. The company has one of the largest research and development teams in the AI and robotics industry. Agile Robots has built a unique portfolio; together with the subsidiaries BÄR Automation, Franka Robotics, idealworks, and Krause Automation, the company covers all areas of AI-driven robotics.

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Zur Position

The AI Teams at Agile Robots are 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.