About the Role
As a senior AI/ML Engineer, you will lead the development of a system that can analyze floorplan images and convert them into 3D geometry. This includes designing and training deep learning models to extract spatial and semantic information from 2D floorplans and developing pipelines to convert detected geometry into structured 3D models.
Key Responsibilities
Design and train deep learning models to extract spatial and semantic information from 2D floorplans (images or vector files). Develop pipelines to convert detected geometry into structured 3D models (e.g., wall objects, door/window placement). Work with vector data (DXF/DWG), 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. Create optimal cabinetry layouts and suggestions from data provided from designers.
Experience Levels
This role is suitable for both mid-level and senior candidates. For mid-level candidates, we are looking for strong experience with deep learning frameworks (PyTorch, TensorFlow) and vision models (YOLO, UNet, Detectron, etc.). Experience in computer vision or document/image parsing is also required. Additionally, an understanding of geometry-based learning and spatial context is essential. Mid-level candidates should be able to translate model output into geometric representations. For senior candidates, we require advanced expertise in geometry-based learning, OCR with spatial context, and complex vision systems. Proven ability to lead ML projects from conception to production is also necessary. Experience with CAD/BIM environments, Rhino/Grasshopper, or geometry processing libraries (e.g., trimesh, Open3D) is desirable. Senior candidates should have a track record of deploying ML models in real-world manufacturing or design environments and project leadership and team mentoring experience.