
Working Student - Data Engineering (m/ f/ d), Munich
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Median für Tech in München: 17,26 €/Std., aus 104 Werkstudentenanzeigen mit Gehaltsangabe der letzten 12 Monate. Gehaltsübersicht
Voraussetzungen
Studium: Informatik, Ingenieurwesen, Mathematik und Statistik oder vergleichbar · Immatrikulation erforderlich
Arbeitszeit & Dauer
20 Std./Woche
Arbeitgeber
Seit März 2026 ist das die einzige Stelle für Studierende von Kyrall in unseren Daten.
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Davon: 31 % ohne Deutschkenntnisse, 56 % hybrid oder remote, 10 % mit Gehaltsangabe.
Skills laut Anzeige
PythonCADData PipelinesB-RepsMeshesPoint Clouds3D Geometry
Stellenbeschreibung
Bewerbung vorbereiten Lebenslauf und Anschreiben passend zu dieser Stelle, kostenlos.
Beschreibung bereitgestellt von Kyrall
We're building the world's fastest way to design real, functional 3D parts. Kyrall's AI-powered design agent turns ideas into ready-to-manufacture 3D models in seconds. Backed by top European VCs, we're a young, well-funded startup based in Munich — and we're just getting started.
The Role
You'll work on our data team that owns the data our models learn from. That means sourcing 3D parametric data, writing parsers for CAD formats, and keeping the pipeline running so the AI team always has clean, usable training data.
What To Expect
- Develop parsers that turn CAD formats into ML-compatible representations
- Source, clean and structure 3D parametric datasets
- Maintain and extend our data pipeline
- Deliver datasets to the AI team and support their experiments
Your Profile
- Studying computer science, engineering, mathematics or similar
- Solid Python skills
- Interest in 3D geometry, CAD or geometric data (B-Reps, meshes, point clouds)
- Structured, self-driven way of working
- 20 hours per week, on-site in Munich
Nice To Have
- Experience with CAD software or libraries
- Familiarity with data pipeline tooling
Why Kyrall?
We're reinventing how machines are designed and built, from the ground up. 3D modeling tools were the last major leap in this space, and the way we design parts today has hit its limit. You'll work directly with the founders and AI team on a small, fast-moving team — and see your work land in the product within weeks.
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