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EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than 6,500 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of more than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries.

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

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 










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