RAG Architectures Intern — Build & Benchmark

D One; Zürich; Hybrid; CHF 20,000 - 27,000; Full time

Benefits offered by this job

Mentoring by senior consultants

D ONE Academy access

Offsite socialising events

Job summary

D ONE is seeking a data-driven student for a fixed-term internship in Zürich, focusing on retrieval-augmented generation (RAG) system design. You will study state-of-the-art methods, build modular Python components, and benchmark configurations across local and cloud environments while communicating results to consultants and clients.

You will work under mentorship with senior D ONE consultants, contribute to a clearly scoped topic, and have opportunities to join the firm as a consultant after a

Qualifications

• Currently enrolled 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.
• Down-to-earth and pragmatic results-oriented attitude.
• Experience in working with large data sets and databases.
• Knowledge in Python, SQL, Git, Spark, cloud platforms.
• Excellent communication skills in English; German is a strong plus.

Responsibilities

• Reviewing the state of the art in retrieval-augmented generation and selecting approaches worth building on.
• Designing and implementing RAG components in clean, modular Python.
• Running the solution across local and cloud environments and reasoning about trade-offs.
• Systematically benchmarking configurations and interpreting results.
• Documenting your work and presenting it to both technical and non-technical audiences.

Skills

Python

SQL

Git

Spark

Cloud platforms

English

German

Education

Bachelor/Master/PhD student

Tools

LangChain

LlamaIndex

Haystack

pgvector

Qdrant

Weaviate

Chroma

FAISS

Job description

D ONE is seeking a data-driven student for a fixed-term internship in Zürich, focusing on retrieval-augmented generation (RAG) system design. You will study state-of-the-art methods, build modular Python components, and benchmark configurations across local and cloud environments while communicating results to consultants and clients.

You will work under mentorship with senior D ONE consultants, contribute to a clearly scoped topic, and have opportunities to join the firm as a consultant after a