Job Description

As a Working Student in the GenAI / LLM team at Cinemo, you will support the evaluation and validation of agentic AI systems and GenAI algorithms for NLP that power next-generation in-car experiences. You will help build datasets, extend evaluation tooling, and contribute to end-to-end testing workflows to ensure our non-deterministic AI components are measurable, reliable, and ready for real-world automotive environments across cloud-based services and in-vehicle platforms such as Android Automotive OS (AAOS) and Linux.

In this role, you will:

• Support evaluation of agentic AI systems and LLM-based NLP features, including qualitative and quantitative analysis.
• Create, curate, and maintain datasets for benchmarking, regression testing, and scenario coverage.
• Extend and improve internal evaluation frameworks (metrics, dashboards, automated test runs).
• Contribute to end-to-end testing of GenAI features within the in-car experience, including integration and validation workflows.
• Document findings, track model/system changes, and communicate results clearly to the team.
• Collaborate with engineers and researchers to translate evaluation insights into actionable improvements.

What you will need to succeed:

• Ongoing Bachelor’s or Master’s studies in Computer Science, AI/ML, Data Science, Computational Linguistics, or a related field.
• Hands-on programming skills in Python and a solid understanding of basic ML/NLP concepts.
• Interest in GenAI / LLMs, agentic systems, and evaluation of non-deterministic AI behavior.
• Experience with data handling and dataset creation (labeling, preprocessing, quality checks).
• Familiarity with software testing concepts (e.g., unit/e2e testing, CI) is a plus.
• Good written and spoken English communication skills.