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Internship - Evaluation of Retrieval-Augmented Generation Systems
Job in
8081, Zurich, Kanton Zürich, Switzerland
Listed on 2026-10-14
Listing for:
D One
Apprenticeship/Internship
position Listed on 2026-10-14
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), Data Engineering, Machine Learning/ ML Engineer, Data Scientist
Job Description & How to Apply Below
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.
- 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.
- 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, Deep Eval, promptfoo, Tru Lens or Lang Smith, 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).
- 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.
- 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?
D ONE Value Creation AG
Sihlfeldstrasse 58
8003 Zürich
Position Requirements
Less than 1 Year
work experience
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