Das ist der Job
Curate and develop high-quality datasets, using synthetic data generation for robust training and evaluation.
Darum lohnt es sich
Collaborate with cross-functional teams to integrate AI components into other systems. Job Description Design, implement, test, and continuously optimize end-to-end RAG pipelines, including data parsing, ingestion, prompt engineering, and chunking strategies.
Rigorously evaluate LLM applications on metrics including correctness, latency, and hallucination. Assist in the deployment of LLM-based applications, analyze user feedback, and contribute to iterative improvements. Write clean, maintainable, and testable code following best practices.
Requirements Master’s or Ph.D. in Computer Science, Machine Learning, or a related field and a minimum of 2 years of hands‑on industry experience in software engineering. Experience operating RAG systems in production environments, including monitoring, debugging, and continuous improvement based on real user behavior.
Solid understanding of software engineering practices applied to AI systems (testing, CI/CD integration, versioning, and reproducibility). Ability to balance research innovation with long‑term maintainability and customer‑ready quality standards. Clear communication and presentation skills. Good To Have Experience with observability stacks (e.g.,
