Design and develop computer vision, image processing, and deep learning algorithms for wafer inspection, defect detection, classification, and die alignment.
Integrate and optimize optical systems, including industrial cameras, lenses, lighting, filters, and vision hardware.
Develop automated calibration and alignment solutions to achieve high-precision wafer inspection.
Build and optimize real-time vision software and integrate vision systems with wafer probers and automation equipment.
Improve image acquisition and processing performance for high-speed, high-volume manufacturing environments.
Evaluate and optimize inspection accuracy through testing, validation, and statistical performance analysis.
Prepare and maintain Bill of Materials (BOM) and support engineering documentation.
Requirements
Bachelor's or Master's Degree in Electrical Engineering, Computer Science, Optical Engineering, Robotics, or a related discipline.
At least 5 years of experience in computer vision, machine vision, or Automated Optical Inspection (AOI) system development, preferably within the semiconductor or industrial automation industry.
Strong programming skills in C++ or Python, with hands-on experience using computer vision libraries such as OpenCV, Halcon, or Matrox Imaging Library (MIL).
Experience with deep learning frameworks such as PyTorch or TensorFlow for image analysis and defect classification.
Good understanding of industrial optics, imaging systems, camera calibration, and illumination techniques.
Experience integrating industrial cameras and vision hardware using GigE Vision, Camera Link, USB3 Vision, CoaXPress, or similar interfaces.
Knowledge of semiconductor wafer inspection, wafer probers, GPU acceleration (CUDA, TensorRT), or related technologies is an advantage.
