Research Engineer/Fellow (Deep Learning Computer Vision - SHNeo)

Singapore Institute of Technology; Singapore; On-site; Full time

Job summary

A University of Applied Learning is seeking a Research Engineer/Fellow for a project on deep learning in computer vision. The role involves developing algorithms for object detection, collaborating with industry partners, and managing project deliverables. Candidates should hold at least a Bachelor’s degree in Computer Science or a related field, with hands-on experience in deep learning frameworks. This position offers the chance to work closely with a research team on innovative industry-driven projects in Singapore.

Qualifications

• Strong technical knowledge and hands-on experience in deep learning frameworks.
• Experience in object detection, classification, and segmentation.
• Good understanding of computer vision techniques.

Responsibilities

• Participate in and manage the research project to ensure timely achievement of deliverables.
• Develop, train, and optimise deep learning models using real-world datasets.
• Prepare project documentation and technical reports.

Skills

Deep learning frameworks (e.g., PyTorch, TensorFlow)

Deep learning models (e.g., YOLO, U‑Net, EfficientNet)

Computer vision techniques and algorithms

Python and relevant libraries (e.g., PyQt, OpenCV)

Industry R&D project experience

Education

Bachelor’s degree in Computer Science or related field

Master’s or PhD degree in relevant areas

Job description

Job Description

Research Engineer/Fellow (Deep Learning Computer Vision - SHNeo)

Posting Start Date: 31/12/2025

Schemes of Service: Research

Division: Professional Officers

Employment Type: Fixed Term

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. The primary responsibility of this role is to support and contribute to an industry innovation research project. The Research Engineer will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and segmentation.

Key Responsibilities

• Participate in and manage the research project together with the PI, Co-PI, and research team to ensure timely achievement of project deliverables.
• Undertake the following specific responsibilities in the project:
• Develop, train, and optimise deep learning models for object detection, classification, and segmentation using real-world datasets.
• Design and implement software modules to integrate the models into a working system prototype.
• Perform data annotation.
• Conduct experiments, analyse results, and iterate models for improved accuracy and efficiency.
• Prepare project documentation, technical reports, and academic publications.
• Collaborate with industry partners and contribute to technology transfer efforts.

Job Requirements

• Possess strong technical knowledge and hands‑on experience in:
• Deep learning frameworks (e.g., PyTorch, TensorFlow)
• Deep learning models (e.g., YOLO, U‑Net, EfficientNet, ResNet, FPN, Fast R‑CNN)
• Computer vision techniques and algorithms
• Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit‑learn), particularly for developing Windows desktop application software incorporating deep learning models
• Hold at least a Bachelor’s degree in Computer Science, Electrical/Electronic/Software Engineering, or a related field.
• A Master’s or PhD degree in relevant areas will be advantageous.
• Familiarity with the following areas is advantageous:
• Participation in Kaggle competitions, showcasing practical problem‑solving and model development skills
• Model deployment (e.g., ONNX, TensorRT)
• Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano)
• Real‑time processing and GPU acceleration
• Experience working on industry R&D projects.

Key Competencies

• Able to build and maintain strong working relationships with team members, stakeholders, and external partners.
• Self‑motivated and committed to continuous learning and improvement.
• Proficient in technical writing & presentation, research reporting, and academic publication.
• Possess strong analytical, problem‑solving, and critical thinking skills.
• Demonstrate initiative and ownership in carrying out tasks independently.