About the Role
As a Deep Learning Engineer, you will lead the development of a system that can analyze floorplan images and convert them into 3D geometry. This includes walls, doors, windows, and more, ready for our production engine.
Your Responsibilities
* Design and train deep learning models to extract spatial and semantic information from 2D floorplans.
* Develop pipelines to convert detected geometry into structured 3D models.
* Work with vector data, PDFs, or raster images to detect key architectural features.
* Collaborate with CAD and backend engineers to translate AI output into parametric geometry.
* Optimize models for speed, accuracy, and usability in real-world production environments.
Requirements
Mid-Level (3-6 years experience)
* Strong experience with deep learning frameworks (PyTorch, TensorFlow) and vision models (YOLO, UNet, Detectron, etc.).
* Experience in computer vision or document/image parsing.
* Understanding of geometry-based learning and spatial context.
* Ability to translate model output into geometric representations.
Senior Level (6+ years experience)
* Advanced expertise in geometry-based learning, OCR with spatial context, and complex vision systems.
* Proven ability to lead ML projects from conception to production.
* Experience with CAD/BIM environments, Rhino/Grasshopper, or geometry processing libraries.
* Track record of deploying ML models in real-world manufacturing or design environments.
Bonus Experience
* Experience with CAD/BIM environments, Rhino/Grasshopper, or geometry processing libraries.
* Knowledge of architectural drawing standards and conventions.
* Experience in manufacturing or design automation industries.
Why This Role is Ideal
* You'll work at the intersection of vision and design automation.
* Your work will significantly reduce the time from inspiration to production in the interiors industry.
* Join a team where AI connects directly to real-world manufacturing.