Computer Vision Engineer
Our client, a leading provider of digital manufacturing solutions for interior spaces, is seeking a talented Computer Vision Engineer to join their team. This is an exciting opportunity to work at the forefront of AI and design automation, developing innovative tools that will revolutionize the interiors industry.
Role Description
As a Computer Vision Engineer, you will be responsible for designing and training deep learning models to extract spatial and semantic information from 2D floorplans. Your work will involve developing pipelines to convert the detected geometry into structured 3D models, ready for integration with the client’s CAD and backend systems. You will collaborate closely with the design automation and engineering teams to bring intelligent layout recognition to life, optimizing models for speed, accuracy, and real-world usability.
Technical Must Have Skills:
- Expertise in Deep Learning Frameworks – Proven experience with deep learning frameworks such as PyTorch and TensorFlow, and a strong understanding of computer vision models like YOLO, UNet, and Detectron.
- Computer Vision and Image Processing – Solid background in computer vision and image processing, with the ability to analyze and extract spatial and semantic information from 2D images and vector data.
- Geometry-based Learning – Experience in geometry-based learning and spatial context understanding, with the ability to translate model output into geometric representations.
- CAD/BIM Integration – Knowledge of CAD/BIM environments, Rhino/Grasshopper, or geometry processing libraries (e.g., trimesh, Open3D) to integrate AI output with design and manufacturing workflows.
- Production Deployment – Proven track record of deploying machine learning models in real-world manufacturing or design environments, with a focus on optimizing for speed and accuracy.
Technical Nice to Have Skills:
- OCR and Spatial Context – Experience in optical character recognition (OCR) with spatial context, to extract information from architectural drawings and documents.
- CAD/BIM Expertise – In-depth knowledge of CAD/BIM environments, Rhino/Grasshopper, or geometry processing libraries, to translate AI output into parametric geometry.
- Manufacturing Automation – Experience in the manufacturing or design automation industries, with an understanding of architectural drawing standards and conventions.
- Project Leadership – Demonstrated ability to lead machine learning projects from conception to production, with experience in team mentoring and collaboration.
- Shader Research – Knowledge of shader research and implementation for WebGL/ThreeJS, to enhance the visual fidelity of 3D outputs.
Additional Functional Requirements:
- Problem-Solving Skills – Ability to tackle complex problems and develop innovative solutions that bridge the gap between AI and real-world manufacturing.
- Collaboration and Communication – Strong interpersonal skills to work effectively with cross-functional teams, including designers, engineers, and product managers.
- Attention to Detail – Meticulous approach to model development and deployment, ensuring high-quality outputs that meet the client’s requirements.
- Adaptability – Willingness to learn and adapt to new technologies, methodologies, and industry standards as the field of computer vision and design automation evolves.
- Passion for Innovation – Genuine enthusiasm for pushing the boundaries of what’s possible in the interiors industry, with a drive to create transformative solutions.
Educational and Certification Requirements:
- Bachelor’s Degree – A bachelor’s degree in Computer Science, Electrical Engineering, or a related technical field.
- Advanced Degree – A master’s degree or a Ph.D. in a relevant discipline is highly desirable.
Job Ref: BBBH26059
Next Steps
If you possess the skills and experience required for this exciting Computer Vision Engineer role, we encourage you to submit your CV today. Our team of recruitment experts will review your application and be in touch to discuss the next steps in the process.
Interested in this Role? Submit your CV today!
Please don’t hesitate to contact any of our team with any questions you may have on Email: [email protected]
