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Senior AI Research Engineer (m/w/d) Foundation Models
Agile Robots Se · Germany, Munich (HQ) · Hybrid · Active · Personio
Job facts
| Field | Value |
|---|---|
| Company | Agile Robots Se |
| Title | Senior AI Research Engineer (m/w/d) Foundation Models |
| Normalized title | - |
| Department / team | AI Solutions / Artificial Intelligence & Data |
| Location | Germany, Munich (HQ) |
| Work model | Hybrid / Hybrid |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Personio |
| Posted / first seen | 2026-03-03 / 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 |
| Work model jobs | Active Hybrid postings. | 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 focused on learning-based robot policies and multimodal foundation models for embodied intelligence. The role centers on designing representations and objectives that map perception and language to robot behavior under real-world uncertainty, with ownership of model-level decisions and behavioral outcomes.
Your Responsibilities
Policy Design: Design and train vision- and language-conditioned robot policies using imitation learning, diffusion-based approaches, or transformer architectures, with clear linkage between representation, objective, and resulting behavior. Model Architecture: Define and adapt model architectures, inductive biases, and training objectives for embodied learning under uncertainty beyond standard fine-tuning workflows. Behaviour Analysis: Analyze policy behavior and failure modes under distribution shift, embodiment constraints, and real-world noise, and refine models to improve robustness and generalization. Learning Pipelines: Own end-to-end learning pipelines from data assumptions through training, evaluation, and controlled real-world validation in collaboration with robotics teams. Integration Collaboration: Collaborate closely with robotics, perception, and platform teams to ensure learned policies align with action spaces, timing constraints, and system-level requirements. Research Awareness: Track and critically evaluate advances in robot learning, multimodal foundation models, and vision-language-action systems, assessing their applicability to embodied intelligence.
Essential Skills
Education: Master’s or PhD in Computer Science, Robotics, AI, or a related technical field. Robot Learning: Hands-on experience designing and training learning-based policies for robotics using imitation learning, reinforcement learning, or hybrid approaches. Multimodal Models: Experience adapting or designing transformer-based, diffusion-based, or vision-language-action models for embodied tasks. Modelling Depth: Ability to reason about representations, objectives, inductive biases, and behavioral trade-offs, including explaining why a model is structured in a particular way. Behavioural Ownership: Demonstrated responsibility for model-level outcomes, including debugging policy failures and improving robustness in real-world or semi-real environments. ML Engineering: Strong Python skills and hands-on experience with modern ML frameworks such as PyTorch or TensorFlow, including implementation of training loops and experimentation workflows. Robotics Context: Understanding of how learned policies interact with perception outputs, action spaces, and physical constraints in robotic systems.
Beneficial Skills
Large-Scale Training: Experience with distributed training, GPU clusters, or large-scale experimentation workflows. Predictive Components: Experience leveraging predictive or world-model elements to improve policy robustness or long-horizon behavior. Embodied Evaluation: Experience validating learned policies on real robotic systems or in high-fidelity simulation with sim-to-real considerations. Research Output: Publications, patents, or deployed systems in robotics, multimodal learning, or embodied AI.
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
| Job ID | 4e8b8a697a61d0609a2b5cbdeef176bd134bcac2 |
| 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 | 2551914 |
| Title | Senior AI Research Engineer (m/w/d) Foundation Models |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Germany, Munich (HQ) |
| Department | AI Solutions |
| Team | Artificial Intelligence & Data |
| Employment Type | full_time |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | — |
| Region | — |
| City | — |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://agile-robots-se.jobs.personio.de/job/2551914?language=en |
| Apply URL | https://agile-robots-se.jobs.personio.de/job/2551914?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 | 2026-03-03 14:09:41Z |
| 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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