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Internship - LLM-Based Information Extraction (Zurich, Switzerland)

On-site work

Publication date: 08/11/2026

In this internship you will work independently on a topic in the area of automated understanding of business documents. You will move from raw, messy documents to structured, verifiable information, and make the approach hold up across domains.

Responsibilities

Reviewing current approaches to information extraction from unstructured and semi-structured documents; Designing and implementing extraction pipelines in clean, modular, well-tested Python; Building annotated data sets and measuring extraction quality rigorously; Handling real-world document variety: layouts, languages, scan quality and edge cases; Documenting your work and presenting it to a technical and a non-technical audience

Requirements

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

Nice to have

Solid NLP foundations, in particular named entity recognition, relation extraction and text classification; Working understanding of large language models and of prompting, structured output and function calling; Experience enforcing schemas on model output (e.g. Pydantic, Instructor, Outlines, JSON Schema, constrained decoding); Familiarity with document parsing and OCR tooling (e.g. docling, unstructured, PyMuPDF, Tesseract, Azure Document Intelligence) and with layout-aware models; Practical skills in annotation: guideline design, gold-standard creation and inter-annotator agreement; Command of extraction metrics: entity-level precision, recall and F1, span matching, and error analysis; Comfort working with German and English documents; further languages are welcome; Awareness of data protection and PII handling, including anonymisation and pseudonymisation techniques; Software engineering discipline: reusable Python packaging, configuration, automated tests and CI

Benefits

An uncomplicated and low noise environment that enables to focus on what matters most; An international team of talented people from diverse backgrounds; Direct mentoring by senior D ONE consultants, plus access to the 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
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