Research Engineer Multimodal AI

SINGAPORE INSTITUTE OF TECHNOLOGY; Singapore; On-site; SGD 80,000 - 100,000; Full time

Job summary

A technology research institute in Singapore seeks a candidate for a research role focused on developing multimodal AI systems for fire detection and safety. The successful applicant will manage research projects, design AI algorithms for various sensors, and ensure compliance with safety regulations. A Bachelor's degree in a relevant field, knowledge of computer vision and machine learning, plus proficiency in Python are essential. Relevant experience in research or internships is desirable, supporting an innovative approach to safety technology.

Qualifications

• Bachelor’s degree in Electrical, Electronics Engineering, Computer Engineering, or closely related discipline.
• Working knowledge of computer vision and deep learning concepts.
• Hands-on experience using Python and at least one deep learning framework.
• Basic experience handling and processing sensor data.
• Familiarity with Linux-based development environments.
• Ability to independently implement, test, and document applied research solutions.

Responsibilities

• Participate in and manage the research project with the PI and the team.
• Develop and deploy multimodal AI algorithms for detection systems.
• Design models for detecting personnel and hazardous situations.
• Implement algorithms for environment perception and path planning.
• Build predictive models for fire intensity forecasting.
• Carry out Risk Assessment and ensure compliance with regulations.
• Coordinate procurement and liaise with vendors.

Skills

Signal processing

Machine learning

Computer vision

Deep learning

Python

Data analysis

Education

Bachelor's degree in relevant field

Tools

PyTorch

TensorFlow

Linux

Job description

Job Purpose

The primary responsibility of this role is to deliver on an industry innovation research project where you will be part of the research team to develop a Multimodal AI for Fire Detection & Safety Systems.

Key Responsibilities

• Participate in and manage the research project with Principal Investigator (PI), Collaborator and the research team members to ensure all project deliverables are met.
• Undertake these responsibilities in the project:
• Develop and deploy multimodal AI algorithms for fire, smoke, and hot-work detection by fusing optical, thermal/infrared, LiDAR, RADAR, and gas sensor data under varying environmental conditions.
• Design computer vision and human-behavior analysis models for detecting personnel, posture, casualties, and hazardous situations, including operation in low-visibility scenarios.
• Implement scene mapping, environment perception, and path-planning algorithms using LiDAR and RADAR data to support evacuation guidance and first-responder navigation.
• Build real-time predictive models for fire intensity and spread forecasting and integrate LLM-based scene description and decision support into an end-to-end deployable system.
• Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations.
• Coordinate procurement and liaison with vendors/suppliers.
• Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.

Job Requirements

• Bachelor’s degree (minimum) in Electrical / Electronics Engineering, Computer Engineering, Computer Science, Robotics, or a closely related discipline, with foundational knowledge in signal processing and machine learning.
• Working knowledge of computer vision and deep learning concepts, including object detection and image-based classification, with hands-on experience using Python and at least one deep learning framework (e.g., PyTorch or TensorFlow).
• Basic experience handling and processing sensor data (e.g., camera, thermal, LiDAR, RADAR, or similar perception sensors) in real-world or laboratory settings.
• Familiarity with Linux-based development environments and standard software tools for data analysis, model training, and evaluation.
• Ability to independently implement, test, and document applied research solutions, with prior experience through projects, internships, or research assistantships considered sufficient.
• Prior experience in publishing is desirable.