• Develop and deploy machine learning models for construction site analytics using video, sensor, and 3D data.
• Design deep learning pipelines for infrastructure defect and object detection, semantic segmentation, and tracking (e.g., using YOLO, Transformers).
• Process and analyse point cloud data for structural modelling, damage detection, and registration using 3D vision techniques.
• Support the development of digital twin environments by integrating 2D/3D data from drones or photogrammetry.
• Participate in end-to-end model development: data collection, model design, training, validation, and deployment.

• Relevant qualification in Computer Engineering, Civil Engineering, or related disciplines with focus on AI or data analytics.
• Knowledge of machine learning, deep learning, and computer vision, especially in 3D data processing.
• Proficient in Python, PyTorch, Scikit-learn, and experience with C++ or other forms of computer language.
• Experience with 3D vision tools like Structure-from-Motion, photogrammetry, and point cloud processing.
• Familiarity with line geometry-based registration and transformer models is a plus.
• Strong analytical, communication, and teamwork skills.
• Exposure to infrastructure or civil engineering inspection workflows is a plus.
• Experience in application of AI for built environment monitoring or digital twin systems.
• Strong problem-solving skills and ability to collaborate with technical and non-technical stakeholders.