A multinational technology powerhouse specializing in high-precision equipment and digital manufacturing solutions for the semiconductor and electronics sectors. With a rich heritage in innovation, the company supports global clients across the end-to-end electronics value chain-from chip assembly and packaging to surface mount technology. Headquartered in Asia, it operates a vast network of R&D and production facilities worldwide, delivering automation, AI-driven process solutions, and sustainable smart factory technologies.
Computer Vision Engineer - Advanced Manufacturing Solutions
Join a high-impact R&D team focused on building state-of-the-art vision solutions for next-generation semiconductor manufacturing and automation systems. As a Computer Vision Engineer, you will develop advanced algorithms and real-time inspection systems to drive improvements in process efficiency, product yield, and quality.
Key Responsibilities:
• Design and implement computer vision algorithms for defect detection, feature recognition, and process automation in semiconductor manufacturing environments.
• Develop and deploy deep learning models to enable high-speed, high-accuracy visual inspection.
• Integrate vision solutions with robotics, automation platforms, and backend semiconductor equipment (e.g., wire bonders, die bonders).
• Create and refine image processing techniques for pattern matching, object tracking, and quality assurance.
• Collaborate with cross-functional teams to enhance real-time inspection capabilities and drive yield improvements.
• Perform data analysis, validate models, and fine-tune algorithm performance to meet rigorous industry standards.
• Optimize system performance with respect to latency, accuracy, and robustness in a production environment.
Requirements:
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, Robotics, or a related field.
• Proven experience in computer vision, image processing, and machine learning.
• Proficiency in Python and C++ with hands-on experience using OpenCV, TensorFlow, or PyTorch.
• Familiarity with deep learning architectures (e.g., CNNs, GANs, Transformers) is a strong advantage.
• Exposure to semiconductor automation, optical inspection, or metrology is beneficial.
• Experience with real-time systems, embedded platforms, or hardware acceleration (e.g., CUDA, FPGA) is a plus.
• Strong problem-solving skills, analytical mindset, and effective communication abilities.
Wilson Tay
Direct Line: 6697 7866
EA License No: 91C2918
Personnel Registration Number: R2091205
