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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Robotic Learning Engineer - **Company:** Agile Robots Ag - **Location:** München, Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Training Data, Agile Methodology, Artificial Intelligence, C++ (Programming Language), Computer Programming, Information Engineering, Data Systems, Python (Programming Language), Machine Learning, Operational Databases, Software Engineering, Systems Architecture, Reinforcement Learning, Model Validation, Information Technology, Machine Learning Operations, Data Pipelines, Data Generation - **Published:** July 25, 2026 - **Apply:** https://www.adzuna.de/details/5813864859 ## About the Role * 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. ## Description The 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., * 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Fireside Chat: Deep Learning, Deep Impact: Harnessing AI for Language Innovation](https://www.wearedevelopers.com/videos/612-fireside-chat-deep-learning-deep-impact-harnessing-ai-for-language-innovation) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Robots are coming into the wild! Full-Stack Robotics Engineers, be ready!](https://www.wearedevelopers.com/videos/479-robots-are-coming-into-the-wild-full-stack-robotics-engineers-be-ready) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Got AI ideas but no money? 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