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Software Developer, circular-construction AI (REON / SXL)

emploi.epfl.ch -
Lausanne, VD

Soumettre votre candidature

Détails de l'emploi

CDD
Il y a 14 jours

Qualifications

Français
Git
Anglais
Niveau Master
Docker
Neo4j
Python
Allemand

Description complète du poste

Mission

The Structural Xploration Lab (SXL) at EPFL is developing REON, an AI system that predicts the reuse value of building components before demolition, turning research validated on 23,200 real reuse-market transactions into a working product. We are looking for a software developer to help build the core of this product alongside the founder: taking a validated research prototype and turning it into a clean, working, deployable tool.

Main duties and responsibilities

Extract and harden a scoring engine from an existing Python/Streamlit prototype into robust, standalone code
Rebuild the data layer from Neo4j to a Python-native graph structure
Implement data-ingestion and similarity-matching logic that completes missing component information (GNN)
Build a lightweight web interface: data upload in, ranked results out
Work independently from rough goals to working software, using modern tooling (including AI coding assistants) to move fast
Keep the codebase clean and documented so it can be extended by others.

Profile

We are looking for a strong early-career Python developer who is interested in bringing a research prototype into a working product. The role combines graph data, ML, and practical web development. Some technologies may be learned during the project, but solid Python skills and hands-on experience with graphs and GNNs are essential.

Degree in computer science, software engineering, data science, machine learning, or an equivalent field; recent graduates are welcome
Strong Python skills and the ability to write clean, modular, tested, and documented code
Hands-on experience with graph data structures and graph neural networks, gained through academic research, internships, professional work, or substantial personal projects
Experience with machine-learning pipelines, including data preparation, model training or inference, and evaluation
Interest in migrating an existing Neo4j model to a custom Python-native graph implementation
Experience building at least one complete application beyond notebooks, including a backend API and a functional web interface
Comfortable learning unfamiliar technologies and improving an existing prototype step by step
Familiar with Git; experience with LLM workflows, Docker, or cloud deployment is an advantage
Self-directed, pragmatic, and motivated by research-to-product development
Valid Swiss work authorisation; holders of an S permit are welcome if authorised to work
Fluent English; French or German is an advantage

We offer

The chance to build the technical core of an EPFL spin-out in formation, in circular construction and AI
Direct collaboration with the founder and real ownership of what you build
A flexible, hands-on role with genuine impact
For the right person, a possible path to a founding technical role at REON
The starting date is flexible and can be agreed upon with the selected candidate

Informations

Activity Rate Min : 20.00

Activity Rate Max : 80.00

Contract Type: CDD

Duration: 2-4 months

Reference: 2351

Soumettre votre candidature

Affinez votre recherche

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Je souhaite recevoir la dernière alerte Emploi pour les postes de ce type : ai workflows (lausanne, vd)

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