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(Senior) AI Research Engineer (m/f/d) Generative Video for Robotics
Agile Robots Se · Germany, Munich (HQ) · Active · Personio
Job facts
| Field | Value |
|---|---|
| Company | Agile Robots Se |
| Title | (Senior) AI Research Engineer (m/f/d) Generative Video for Robotics |
| Normalized title | - |
| Department / team | AI Solutions / Artificial Intelligence & Data |
| Location | Germany, Munich (HQ) |
| Work model | - |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Personio |
| Posted / first seen | 2026-04-20 / 2026-05-30 |
| Changed / last seen | 2026-05-30 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Agile Robots Se. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Personio. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| Department jobs | Active postings in AI Solutions. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Agile Robots Se |
| Source | bcb1fbae-6077-4ee3-833d-67baf488bf90 |
| ATS provider | Personio |
Description
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.
Full job record
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| Org ID | cbcab16d-d77f-4aae-95e4-f537194009c8 |
| Source ID | bcb1fbae-6077-4ee3-833d-67baf488bf90 |
| Board ID | bcb1fbae-6077-4ee3-833d-67baf488bf90 |
| Provider | personio |
| Provider Job Key | 2606934 |
| Title | (Senior) AI Research Engineer (m/f/d) Generative Video for Robotics |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Germany, Munich (HQ) |
| Department | AI Solutions |
| Team | Artificial Intelligence & Data |
| Employment Type | full_time |
| Workplace Type | — |
| Remote Policy | — |
| Country | — |
| Region | — |
| City | — |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://agile-robots-se.jobs.personio.de/job/2606934?language=en |
| Apply URL | https://agile-robots-se.jobs.personio.de/job/2606934?language=en |
| First Seen At | 2026-05-30 06:05:02Z |
| Last Seen At | 2026-06-06 07:54:12Z |
| Last Checked At | 2026-06-06 07:54:12Z |
| Last Changed At | 2026-05-30 06:05:02Z |
| Inactive At | — |
| Source Posted At | 2026-04-20 13:54:46Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=personio/board=agile-robots-se.de/date=2026-06-06/2026-06-06T07-54-11-954Z-784a826e6f3211779d98f861e26fa61d9ac5e980c0b6fc37cf918f969809edb8.json |
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