Internship - Evaluation of Retrieval-Augmented Generation Systems

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