Internship - Evaluation of Retrieval-Augmented Generation Systems (Zurich)

Fixed-term contract (typically 3 months) · 80–100% · Zürich · Students (Bachelor, Master or PhD level) «Making sense of data is the winning competence in all industries.» We build D ONE with the belief that every company will be a data company. Since our beginnings, we help our clients to make sense of their data and generate value. In this internship you will work independently on a topic in the area of evaluating generative AI systems. You will turn fuzzy questions about quality into measurements that people trust, and make those measurements repeatable. Your tasks will include: Reviewing evaluation methodology for retrieval-augmented and generative systems. Designing and implementing automated evaluation logic in Python. Building and curating test data sets, including gold standards and synthetic cases. Analysing results statistically and turning them into clear, defensible conclusions. Documenting your work and presenting it to a technical and a non-technical audience. What you bring: Current enrolment in a Bachelor's, Master's or PhD programme in Computer Science, Data Science, Computational Linguistics, Engineering, Mathematics or a comparable field. Interest in at least one industry domain and curiosity about how data creates value in it. Down-to-earth and pragmatic results-oriented attitude. Experience in working with large data sets and databases. Knowledge in relevant technologies and programming languages (e.g. Python, SQL, Git, Spark, cloud platforms). Excellent communication skills in English; German is a strong plus. Preferred qualifications: Working understanding of large language models and retrieval-augmented generation, and of where such systems typically fail. Familiarity with evaluation concepts such as faithfulness, groundedness, answer relevance, context precision and recall, and hallucination detection. Exposure to evaluation tooling such as RAGAS, DeepEval, promptfoo, TruLens or LangSmith, or a willingness to build equivalent logic yourself. Experience with LLM-as-a-judge techniques, and a healthy scepticism about their reliability. Solid statistical foundations: sampling, significance testing, confidence intervals, inter-annotator agreement. Practical skills in test-set construction, annotation guidelines and synthetic data generation. Software engineering discipline: reusable Python packages, automated test suites, CI, reproducible experiment pipelines. Ability to communicate quantitative results visually and concisely (e.g. pandas, plotly, matplotlib, dashboards). What we offer: An uncomplicated and low noise environment that enables to focus on what matters most. An international team of talented people from diverse backgrounds that have ambitions, always enjoy an additional challenge, and know how to have fun at work. Direct mentoring by senior D ONE consultants, plus access to our D ONE Academy including knowledge sharing sessions, expert and working groups. A clearly scoped topic that is yours to own, with the freedom to shape how you approach it. Frequent offsite socialising events. A realistic path to joining D ONE as a consultant after a successful internship. To be successful in this role you will need to: Strive to understand your clients' needs. Deliver outstanding results with high business value in a comprehensible form. Have the intellectual agility required to get the job done in an easy-to-do-business-with way. Value clever and creative team play. Work independently and structure your own progress, while knowing when to pull in a senior colleague. Are you interested in joining a great team with a proven track record and to work on a topic that will constantly challenge you? We are happy to receive your application with reference: D ONE Value Creation AG Sihlfeldstrasse 58 8003 Zürich