AI Engineer

GRC Construction Pte. Ltd.; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

GRC Construction Pte. Ltd. is seeking a skilled ML/AI engineer to develop and deploy large language models for on-site construction data, enabling rapid Q&A and compliance checks across contracts, reports and safety manuals.

The role focuses on edge deployment and integration with IoT-enabled sites. You will gather data from ERP systems, project management tools, and sensor networks, clean and label large datasets, and transform them into production-ready formats.

Qualifications

• Degree in Civil Engineering, Computer Engineering, or related field
• Minimum 3 years of experience building and deploying ML models in production
• Experience in AEC industry desirable but not mandatory with strong AI portfolio
• Proficiency in Python, Java; strong coding practices (Git)
• Deep experience with TensorFlow and PyTorch
• Familiarity with LangChain, LlamaIndex, and vector databases for RAG
• Data processing with SQL and related libraries
• Experience with BIM software or IFC formats
• Stay current with ConTech research and apply cutting-edge techniques

Responsibilities

• Model development and deployment for construction drawing recognition and take-off
• Data gathering, cleaning, labeling from ERP, PM software, and sensor networks
• Productization and MLOps: production-ready APIs and scalable services
• Collaborate with digitalisation engineers and end users to improve accuracy and reliability

Skills

Python

Java

Git

TensorFlow

PyTorch

LangChain

LlamaIndex

Vector DB

SQL

BIM

IFC

Education

Civil Engineering / Computer Engineering degree

Tools

ERP systems

Project management software

Code collaboration (Git)

Job description

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