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# Senior AI Scientist

- **Company:** HUK-COBURG Versicherungsgruppe
- **Location:** Coburg, Germany (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Programming, Python (Programming Language), Machine Learning, Cloud Platform System, Pytorch, Large Language Models, Multi-Agent Systems, Information Technology, Low Latency, HuggingFace
- **Published:** August 29, 2026
- **Apply:** https://www.adzuna.de/details/5802885427

## About the Role

* A degree with above-average grades (at least a master's, ideally a Ph.D.) in computer science, mathematics, statistics, physics, or a comparable quantitative field
 * Several years of experience in data science, machine learning, or AI engineering, as well as in the development of production-ready AI systems
 * A solid understanding of the statistical and mathematical foundations of modern machine learning methods, particularly statistical inference, probability theory, experimental design, and causal modeling
 * Excellent programming skills in Python, as well as hands-on experience with modern ML and DL frameworks (e.g., PyTorch, Hugging Face, or comparable technologies)
 * Practical experience in developing agentic AI systems with LLMs, including RAG, tool calling, structured outputs, reasoning workflows, and multi-agent systems
 * Deep understanding of LLM and agent architectures at the system level, including agent orchestration, planning, inference optimization, context management, evaluation of agent behavior, and scaling of production-ready AI systems
 * Hybrid work model: Willingness to work on-site in Coburg

## Description

* Design and implementation of machine learning and GenAI solutions for business processes in the insurance industry-from claims management to customer service and internal processes
 * Development and optimization of (agentic) AI systems based on modern LLMs
 * Architecture, implementation, and operation of production-ready AI frameworks in cloud environments
 * Development of statistical methods and evaluation frameworks to measure quality, robustness, and business impact
 * Optimization of model inference, latency, and resource efficiency for scalable AI applications
 * Close collaboration with engineering, product teams, and business units to transition prototypes into production systems


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