Senior Engineer / Assistant Manager (AI)

Responsibilities

• Lead the design and development of computer vision-based AI solutions focused on detecting unsafe worker behaviors (e.g., not wearing helmets, no safety harness, unauthorized access) and identifying high-risk construction activities (e.g., working at heights, hot work, deep excavation).- Develop end-to-end visual recognition pipelines using streaming video data from CCTV systems, body-worn cameras, drones, and other on-site sources.- Design, train, and optimize deep learning models for object detection, human pose estimation, action recognition, and anomaly detection with high accuracy and low latency.- Drive AI models from prototype to production deployment, including model optimization for edge computing devices and integration with existing infrastructure.- Collaborate closely with product managers, hardware engineers, and field operations teams to understand site-specific challenges and ensure practical AI deployment.- Build and manage data workflows, including data collection, labeling, augmentation, quality control, and versioning for large-scale training datasets.- Stay up to date with cutting-edge research (e.g., Vision Transformers, self-supervised learning, few-shot learning) and apply innovative techniques to improve model generalization and cross-scene adaptability.- Mentor junior AI engineers and establish best practices for efficient, scalable, and maintainable AI development.

Requirements

• Degree or Higher Diploma in Computer Science, Artificial Intelligence, Pattern Recognition, Automation or related disciplines.- Minimum of 5 years of professional experience in AI, with a strong focus on computer vision and deep learning.- Proven experience in delivering AI solutions from concept to production, especially in real-world applications.- Proficient in deep learning frameworks such as Py. Torch or Tensor. Flow, and experienced with computer vision libraries like OpenCV, MMDetection, MMPose, YOLO, etc.- Solid understanding of core vision tasks: object detection, pose estimation, action recognition, and video analysis.- Hands-on experience with video stream processing (RTSP, ONVIF), multi-camera fusion, and model deployment on edge devices (e.g., NVIDIA Jetson, Huawei Atlas).- Familiarity with model optimization techniques for low-latency and resource-constrained environments (e.g., TensorRT, OpenVINO, NCNN).- Demonstrated ability to lead small technical teams and manage project timelines independently.- Strong ability to read technical literature and write clear documentation in English.- Experience in smart construction sites, industrial safety monitoring, or video surveillance systems is highly preferred.- Prior exposure to construction environments or field testing is a strong plus.- Experience with drone-based video analysis or multi-modal fusion (vision + sensors) is advantageous.- Publication record in top-tier conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, AAAI) is a bonus. Apply now