As a Computer Vision Engineer, you will design and implement advanced vision solutions that power high-precision semiconductor manufacturing and automation. Your work will focus on cutting-edge image processing, machine learning algorithms, and real-time vision inspection systems to drive improvements in efficiency, yield, and product quality.
- Algorithm Development: Design, develop, and optimize computer vision algorithms for defect detection, feature recognition, and automation in semiconductor manufacturing.
- Deep Learning Integration: Implement and deploy deep learning-based vision models for high-speed, high-accuracy inspection processes.
- System Integration: Integrate vision systems with robotics, automation platforms, and semiconductor backend equipment (e.g., wire bonders, die bonders).
- Image Processing: Develop and fine-tune techniques for pattern recognition, object tracking, and quality inspection.
- Cross-Functional Collaboration: Work closely with engineering, automation, and production teams to enhance real-time vision inspection and improve yield.
- Performance Optimization: Conduct data analysis, model validation, and performance tuning to meet industry standards and optimize system latency, accuracy, and robustness.
Requirements
- Education: Bachelor's or Master's degree in Computer Science, Electrical Engineering, Robotics, or related fields.
- Technical Expertise:Strong experience in computer vision, image processing, and machine learning.
- Proficiency in Python, C++, and frameworks such as OpenCV, TensorFlow, or PyTorch.
- Hands-on experience with deep learning models (CNNs, GANs, Transformers) for vision tasks is a plus.
- Domain Knowledge: Familiarity with semiconductor automation, optical inspection, or metrology is advantageous.
- Hardware Acceleration: Knowledge of real-time processing, embedded systems, and hardware acceleration (CUDA, FPGA, etc.) is a plus.
- Soft Skills: Strong analytical, problem-solving, and communication skills.