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