$ cat jobs/applied-ai-engineer-intern-m-f-d-sixt-d26cfce0fd32.json
Applied AI Engineer Intern (m/f/d)
Are you passionate about building intelligent systems that make a real impact at scale? As an Applied AI Engineer Intern (m/f/d) at SIXT, you will design and build AI-powered solutions that transform how one of Europe's leading mobility companies operates globally — from intelligent automation to agentic workflows and predictive systems. Working alongside experienced engineers in our Headquarter, you will turn complex challenges into working prototypes and see your solutions deployed in a real production environment. This internship requires a minimum commitment of 6 months and is open to Master's students in a technical field only. Ready to shape the next generation of AI-driven innovation? Apply now and join Team Orange! YOUR ROLE AT SIXT You support the design and development of scalable, production-ready AI automation frameworks and agentic workflows that integrate into SIXT's technology ecosystem You help translate complex business challenges into technical solutions, exploring agentic architectures, MCP integrations, predictive models, and neural networks You contribute across the full product lifecycle — from prototyping and API development to deployment — in close collaboration with our Software Engineering teams You experiment with and benchmark modern GenAI frameworks, evaluate the most effective approach for a given problem, and share your learnings with the team You write clean, well-structured Python code and actively contribute to our tech stack You collaborate with engineers and business leaders, turning requirements into impactful, working data products YOUR SKILLS MATTER Academic Background You are currently enrolled in a Master's program in a STEM field (e.g. Computer Science, Data Science, Mathematics, Physics, or Engineering) and bring a strong technical foundation, with strong academic performance Programming You write clean Python code and have a solid understanding of core computer science and machine learning concepts, demonstrated through un
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