AI Engineer

Job Scopes 1) Model Development & Deployment • Implement & fine tune Large Language Models for construction drawing component recognition, quantity take off. • Develop predictive analytics models to forecast project risks, material delivery bottleneck and so on. • Build and fine-tune Large Language Models (LLMs) or RAG (Retrieval-Augmented Generation) systems to process unstructured data like construction contracts, inspection reports, and safety manuals for instant Q&A and compliance checking. • Optimize models for edge deployment on IoT devices or local servers on-site where internet connectivity is unreliable. 2) Data Engineering & Preparation • Gather data from ERP systems and project management software, and sensor networks. • Cleaning, labelling, and transforming large datasets into usable formats for model training 3) Productization & MLOps • Move models from proof-of-concept to production, ensuring they are scalable, maintainable. Performance monitoring of the production environment. • Build APIs and microservices to serve model predictions to front-end applications used by Project Managers, Safety Officers, and Quantity Surveyors. 4) Collaboration & Optimization • Collaborating with digitalisation engineers & end users to refine models for better accuracy, speed, and reliability. Requirements: (Qualification & Experience) • Recognized degree in Civil Engineering or Computer Engineering or equivalent Engineering field or any other specialization relating to Construction Management. • Minimum of 3 years' of experience in building and deploying machine learning models in a production environment. • Experience in the AEC (Architecture, Engineering, and Construction) industry is highly desirable but not mandatory if you have a strong portfolio working with AI Models • Programming: Proficient in Python, Java or similar languages. Strong coding practices in a collaborative environment (Git, code reviews). • ML Frameworks: Deep experience with TensorFlow, PyTorch. • Generative AI: Familiarity with LangChain, LlamaIndex, and vector databases for building RAG applications. • Data Processing: Proficiency with SQL and data manipulation libraries. • Experience with BIM (Building Information Modeling) software or IFC file formats. • Stay current with the latest research in ConTech (Construction Technology) and apply cutting-edge techniques to improve safety, quality, and efficiency