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PropX

AI/ML Engineer

PropX
Austria · Full-time · Entry

About the role

We are looking for an AI/ML Engineer to build production AI systems that power PropX's Digital Twin platform, specifically designed for managing entire building portfolios and automating ESG intelligence. You will develop computer vision models, knowledge graph–based retrieval systems, and LLM-powered applications that transform geospatial, BIM, and infrastructure data into actionable intelligence.


What you'll do

  • Fine-tune computer vision models 
  • Build a RAG pipeline on a graph database
  • Run a local small language model and escalate to a larger model when needed
  • Set up model versioning, scheduled retraining, and rollback, so regressions get caught before they ship
  • Build APIs that hand model outputs, with confidence and source attached, to the rest of the backend


Minimum qualifications

  • Master's in AI / ML or related fields
  • Programming experience specifically in  Python, APIs, SQL, Git, testing, Docker.
  • Experience fine-tuning a pretrained computer vision model (detection or segmentation) on a real dataset
  • Experience building a RAG pipeline: retrieval, prompting, grounding output in retrieved data
  • Experience running an open-weight LLM (Mistral, Llama, Phi-3, or similar), not just calling a hosted API
  • Experience versioning, monitoring, or rolling back a model in production
  • Experience designing an API that other services depend on


Preferred qualifications

  • Experience with satellite or street-level imagery
  • Graph-based RAG using Neo4j / knowledge graph / vector search.
  • Experience with a cloud platform (AWS, GCP, or Azure) and Docker in a live deployment


Submit your application by 20 July 2026. Applications will be reviewed on a rolling basis, so early applications are encouraged.



Key Skills

Ranked by relevance

computer vision ai python docker neo4j cloud git sql aws gcp
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Posted
Jul 03, 2026
Type
Full-time
Level
Entry
Location
Vienna
Company
PropX

Industries

Software Development

Categories

Engineering Information Technology

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