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Senior AI Research Engineer (m/f/d) Learning-Based Robotics

Agile Robots Se

Germany, Munich (HQ) permanent

Posted: March 2, 2026

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Quick Summary

A Senior AI Research Engineer with strong experience in learning-based methods for robotics and sequential decision-making is needed to develop predictive and learning-based components for embodied systems in collaboration with robotics, perception, and systems teams.

Job Description

About the role:
The AI Research Division of Agile Robots is looking for a Senior AI Engineer with strong experience in learning-based methods for robotics and sequential decision-making, focused on developing predictive and learning-based components for embodied systems in collaboration with robotics, perception, and systems teams.


Your Responsibilities:
• Learning Models: Research and develop learning-based models for robotic and embodied systems.
• Predictive Modelling: Design, train, and evaluate predictive or dynamics-related models.
• Pipeline Integration: Integrate learned models with control, planning, or policy-learning pipelines.
• Experimental Evaluation: Design robotic experiments and conduct scientific evaluation of model performance.
• Collaboration: Collaborate closely with Robotics, Perception, and Systems teams.
• Research Transfer: Contribute to publications, prototypes, and technology transfer into products.


Essential Skills:
• Professional Experience: Minimum of 4 years of professional experience in AI, deep learning, and/or robotics.
• Sequential Learning: Strong background in sequential prediction, dynamics modelling, or model-based learning.
• Temporal Data: Demonstrated experience building and training deep learning models for temporal data such as video, trajectories, or state sequences.
• ML Engineering: Solid Python programming skills and hands-on experience with PyTorch.
• Embodied Systems: Hands-on experience with robotic systems or embodied agents.
• Education: MSc or PhD in Robotics, AI, Computer Science, or a related field.


Beneficial Skills:
• Research Output: Publications or preprints in top-tier ML or robotics venues such as NeurIPS, ICLR, ICML, CoRL, RSS, or ICRA.
• Advanced Modelling: Experience with latent dynamics models, model-based reinforcement learning, or predictive control.
• Sequence Architectures: Familiarity with transformer-based or diffusion-based sequence models.
• Applied Robotics ML: Prior experience applying machine-learning methods in robotics contexts.


What we offer:
• 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 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 facilities with a rooftop terrace overlooking Munich, free drinks & fruits, and regular company events contribute to a good working environment

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