Computer Vision Engineer Roles and Responsibilities
- Design, develop, and optimize computer vision algorithms for defect detection, feature recognition, and automation in semiconductor manufacturing.
- Implement deep learning-based vision models for high-speed and high-accuracy inspection processes.
- Integrate vision systems with robotics, automation platforms, and semiconductor backend equipment (e.g., wire bonders, die bonders).
- Develop and fine-tune image processing techniques for pattern recognition, object tracking, and quality inspection.
- Work closely with cross-functional teams to enhance real-time vision inspection and improve production yield.
- Conduct data analysis, model validation, and performance tuning to meet industry standards.
- Optimize vision system performance in terms of latency, accuracy, and robustness.
Requirements:
- Strong experience in computer vision, image processing, and machine learning.
- Proficiency in Python, C++, OpenCV, TensorFlow, or PyTorch for vision-related applications.
- Experience with deep learning models (CNNs, GANs, Transformers) for vision tasks is an added advantage.
- Familiarity with semiconductor automation, optical inspection, or metrology is advantageous.
- Knowledge of real-time processing, embedded systems, and hardware acceleration (CUDA, FPGA, etc.) is an added advantage.
