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# (Senior) AI Engineer

- **Company:** Ai-driven
- **Location:** München, Germany
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Continuous Integration, Dynamical Systems, Software Product Management, Software Deployment, Software Engineering, Reinforcement Learning, Google Cloud, Large Language Models, Multi-Agent Systems, Fastapi, Containerization, Kubernetes, Information Technology, Machine Learning Operations, Restful APIs, Data Pipelines, Docker, Microservices
- **Published:** August 2, 2026
- **Apply:** https://www.careerjet.de/jobad/de7cef5655dc20751dfa1b9e403e40b830

## About the Role

* Master's or PhD in Computer Science, Software Engineering, or related discipline, with 3-6+ years of hands-on experience in AI/ML development
 * Proven experience with LLM production deployment, MLOps, and CI/CD pipelines on cloud platforms, including containerization, model deployment as scalable APIs, monitoring, drift detection, and security
 * Strong expertise with AI tools, LLM providers, implementing RAG, agents/MCP, multi-agent architectures, SFT/RFT, and LLM-as-a-judge metrics
 * Expertise with one or several advanced AI topics such as simulation of dynamic systems, world models, reinforcement learning, planning and control theories, physics-informed models, robotics/mechatronics
 * Excellent written and verbal communication skills in English, with the ability to collaborate effectively across multidisciplinary teams

## Description

As (Senior) AI Engineer (m/f/d) you will be at the forefront of building our AI product from the ground up. You'll develop cutting-edge AI solutions that power physical R&D automation, working directly with our founding team to shape the future of AI-driven multidisciplinary system design.
Your Role

 * Develop and deploy advanced AI solutions (LLM and non-LLM) at the forefront of physical R&D automation and system design in mechatronics and robotics
 * Design, implement, and test innovative approaches for advanced AI reasoning, leveraging our proprietary ontology and algorithms combined with public tools and data
 * Build and maintain production-ready MLOps infrastructure using cloud platforms (Azure, AWS, GCP), implementing scalable API microservices with Docker, Kubernetes, and FastAPI
 * Work closely with various stakeholders, such as AI and Data Engineers, Product Managers, Chief Officers and Software Teams, to build data pipelines and integrate AI features into user-facing products
 * Implement and optimize RAG systems, multi-agent architectures, and fine-tuning pipelines (SFT/RFT) while addressing biases, hallucinations, and LLM evaluation metrics


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