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
Engineer Computer Vision • Singapore, Singapore