Visual Systems Engineer

• Design and enhance computer vision algorithms for identifying defects, recognizing features, and driving automation in semiconductor manufacturing processes.
• Develop and deploy deep learning-based models to enable fast, precise inspection tasks.
• Integrate vision technologies with robotic systems, automation platforms, and backend semiconductor tools such as wire bonders and die bonders.
• Create and refine image processing methods for tasks like pattern detection, object localization, and quality control.
• Collaborate with multidisciplinary teams to advance real-time vision inspection systems and support production yield improvements.
• Perform data analysis, validate model performance, and adjust parameters to comply with industry benchmarks.
• Optimize vision system efficiency by minimizing latency and maximizing accuracy and reliability.

Requirements of the role:

• A Bachelors or Masters degree in Computer Science, Electrical Engineering, Robotics, or a closely related discipline.
• Solid background in computer vision, image analysis, and machine learning techniques.
• Skilled in developing vision applications using Python, C++, and libraries such as OpenCV, TensorFlow, or PyTorch.
• Hands-on experience with deep learning architectures (e.g., CNNs, GANs, Transformers) is a strong asset.
• Experience or familiarity with semiconductor manufacturing, optical inspection systems, or metrology is beneficial.
• Understanding of real-time computing, embedded platforms, and hardware-accelerated processing (e.g., CUDA, FPGA) is desirable.
• Excellent analytical thinking, problem-solving abilities, and effective communication skills.