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

About the role

Singapore Institute of Technology (SIT), a University of Applied Learning, is recruiting a Research Engineer/Fellow for its Research Division under the SHNeo scheme. The role is fixed term and focuses on supporting an industry innovation research project. The Research Engineer works closely with the Principal Investigator, 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 with the PI, Co-PI and team to meet project deliverables on time.
• 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.
• Run experiments, analyse results and iterate models for better accuracy and efficiency.
• Prepare project documentation, technical reports and academic publications.
• Collaborate with industry partners and contribute to technology transfer.

Required profile

• Bachelor's degree in Computer Science, Electrical/Electronic/Software Engineering or a related field; a Master's or PhD is advantageous.
• Strong technical knowledge and hands-on experience with deep learning frameworks and models.
• Ability to build relationships with team members, stakeholders and partners, and to write and present technically.

Required skills

• Deep learning frameworks such as PyTorch and TensorFlow
• Models such as YOLO, U-Net, EfficientNet, ResNet, FPN and Fast R-CNN
• Python and libraries such as PyQt, OpenCV, NumPy and scikit-learn, especially for Windows desktop applications
• Advantageous: Kaggle experience, model deployment (ONNX, TensorRT), edge/embedded vision (NVIDIA Jetson Nano), real-time processing and GPU acceleration, and industry R&D experience