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Senior AI Research Engineer - Foundation Models(m/w/x)
Designing vision- and language-conditioned robot policies using transformers or diffusion models. Master's or PhD in CS, Robotics, or AI required. 100 EUR net per month bonus.
Requirements
- Master’s or PhD in Computer Science, Robotics, AI, or related field
- Designing and training learning-based policies for robotics
- Adapting or designing transformer-based, diffusion-based, or vision-language-action models
- Reasoning about representations, objectives, inductive biases, and trade-offs
- Responsibility for model-level outcomes, debugging policy failures, improving robustness
- Strong Python skills and ML framework implementation
- Understanding of learned policies interaction with perception, action spaces, and constraints
- Experience with distributed training, GPU clusters, or large-scale experimentation
- Leveraging predictive or world-model elements for policy improvement
- Validating learned policies on real robotic systems or high-fidelity simulation
- Publications, patents, or deployed systems in robotics, multimodal learning, or embodied AI
Tasks
- Design vision- and language-conditioned robot policies
- Train policies using imitation learning, diffusion-based approaches, or transformers
- Link representation, objective, and resulting behavior
- Define and adapt model architectures and training objectives
- Incorporate inductive biases for embodied learning under uncertainty
- Analyze policy behavior and failure modes
- Refine models to improve robustness and generalization
- Manage end-to-end learning pipelines
- Ensure data assumptions through training and evaluation
- Conduct controlled real-world validation with robotics teams
- Collaborate with robotics, perception, and platform teams
- Align learned policies with action spaces and timing constraints
- Track advances in robot learning and multimodal foundation models
- Evaluate applicability of new research to embodied intelligence
Work Experience
- approx. 4 - 6 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- TensorFlow
- Transformer-based models
- Diffusion-based models
- Vision-language-action models
Benefits
Learning & Development
- Development opportunities
Diverse Work
- Challenging tasks
Purpose-Driven Work
- Impactful projects
Corporate Discounts
- Corporate Benefits Program
Additional Allowances
- 100 EUR net per month
Modern Office
- Modern office facilities
Startup Environment
- Rooftop terrace
Snacks & Drinks
- Free drinks
- Free fruits
Team Events
- Company events
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Senior AI Research Engineer - Foundation Models(m/w/x)
Designing vision- and language-conditioned robot policies using transformers or diffusion models. Master's or PhD in CS, Robotics, or AI required. 100 EUR net per month bonus.
Requirements
- Master’s or PhD in Computer Science, Robotics, AI, or related field
- Designing and training learning-based policies for robotics
- Adapting or designing transformer-based, diffusion-based, or vision-language-action models
- Reasoning about representations, objectives, inductive biases, and trade-offs
- Responsibility for model-level outcomes, debugging policy failures, improving robustness
- Strong Python skills and ML framework implementation
- Understanding of learned policies interaction with perception, action spaces, and constraints
- Experience with distributed training, GPU clusters, or large-scale experimentation
- Leveraging predictive or world-model elements for policy improvement
- Validating learned policies on real robotic systems or high-fidelity simulation
- Publications, patents, or deployed systems in robotics, multimodal learning, or embodied AI
Tasks
- Design vision- and language-conditioned robot policies
- Train policies using imitation learning, diffusion-based approaches, or transformers
- Link representation, objective, and resulting behavior
- Define and adapt model architectures and training objectives
- Incorporate inductive biases for embodied learning under uncertainty
- Analyze policy behavior and failure modes
- Refine models to improve robustness and generalization
- Manage end-to-end learning pipelines
- Ensure data assumptions through training and evaluation
- Conduct controlled real-world validation with robotics teams
- Collaborate with robotics, perception, and platform teams
- Align learned policies with action spaces and timing constraints
- Track advances in robot learning and multimodal foundation models
- Evaluate applicability of new research to embodied intelligence
Work Experience
- approx. 4 - 6 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- TensorFlow
- Transformer-based models
- Diffusion-based models
- Vision-language-action models
Benefits
Learning & Development
- Development opportunities
Diverse Work
- Challenging tasks
Purpose-Driven Work
- Impactful projects
Corporate Discounts
- Corporate Benefits Program
Additional Allowances
- 100 EUR net per month
Modern Office
- Modern office facilities
Startup Environment
- Rooftop terrace
Snacks & Drinks
- Free drinks
- Free fruits
Team Events
- Company events
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Agile Robots
Industry
Research
Description
The company develops systems that combine force-moment-sensing and image-processing technology for robotic solutions.
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