About the role
The AI Research Division of Agile Robots is looking for a (Senior) AI Research Engineer (m/f/d) focused on generative video and multimodal sequence modelling for robotics. In this role, you will develop temporally coherent generative models that support simulation, synthetic data generation, and downstream robot learning.
Your Responsibilities
- Video Modelling: Build and optimize generative video models for robotics use cases such as synthetic data generation, predictive sequence modelling, and learning from embodied interaction.
- Multimodal Learning: Develop models that combine video with text, proprioception, and other structured signals to improve temporal reasoning and downstream usefulness.
- Evaluation: Design benchmarks and experiments that assess temporal coherence, sequence quality, and the practical value of generated outputs for robotics learning workflows.
- Data Pipelines: Build scalable training pipelines for large-scale video and sequence datasets with attention to quality, performance, and reproducibility.
- Research Translation: Apply advances in generative modelling, sequence learning, and multimodal AI to improve robotics-focused internal systems and research workflows.
- Collaboration: Work closely with robotics, simulation, and research teams to connect model development with real system constraints and applied use cases.
Essential Skills
- Generative Video: Hands-on experience building generative video or temporal sequence models, including conditional generation, multimodal fusion, and temporal consistency optimization.
- Model Architectures: Strong practical knowledge of modern generative and sequence-modelling approaches such as diffusion models, autoregressive transformers, VAEs, GANs, or DiT-style architectures.
- Temporal Reasoning: Deep understanding of temporally coherent video generation, long-horizon sequence behaviour, and evaluation methods for predictive quality and stability.
- ML Engineering: Strong Python and PyTorch skills, including implementation of training pipelines, large-scale experimentation, and performance-oriented model development.
- Experimentation: Experience designing, running, and interpreting benchmarks on large-scale video datasets with clear judgment around model quality and failure modes.
Beneficial Skills
- Robotics Applications: Familiarity with robotics-adjacent use cases such as simulation, synthetic data generation, or embodied learning workflows.
- Robot Data Modalities: Exposure to robot-relevant signals such as proprioception, force, tactile input, or other structured non-visual data used in embodied systems.
- Deployment Awareness: Experience bringing generative or multimodal models into production or production-near environments with attention to inference efficiency and scalability.
- Research Output: Publications, patents, or applied research contributions in generative modelling, multimodal learning, robotics, or computer vision.
What we offer
- 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 facilites with a rooftop terrace overlooking Munich, free drinks & fruits, and regular company events contribute to a good working environment.