Job Overview
Our client, a global leader in electronics/precision manufacturing, is seeking a highly skilled Wafer Tester Vision Engineer to design, develop, and optimize automated vision inspection systems for semiconductor wafers. In this role, you will implement advanced computer vision algorithms and integrate high-resolution optical hardware into automated wafer probers and inspection testers. Your work will directly impact factory yield by ensuring rapid, precise detection of microscopic defects, layout anomalies, and alignment deviations on the wafer surface.
Key Responsibilities
- Algorithm Development: Design and deploy advanced computer vision, image processing, and deep learning algorithms for wafer defect detection, classification, and die alignment.
- Optical System Integration: Specify, select, and integrate optical hardware components, including high-speed industrial cameras, specialized lenses, filters, and lighting/illumination systems.
- Calibration & Alignment: Develop automated calibration routines for camera-to-motion coordinates, ensuring sub-micron accuracy in probe-to-pad alignment on wafer testers.
- Software Development: Write high-performance, real-time vision processing code and integrate vision pipelines with wafer prober control software and APIs.
- Data & Image Optimization: Optimize image acquisition pipelines for high-throughput wafer testing, minimizing motion blur and maximizing contrast on reflective silicon surfaces.
- Performance Testing & Tuning: Evaluate and benchmark inspection accuracy (reducing false positives/negatives) using statistical process metrics.
- BOM Loading: Collect materials and submit BOM lists on the development system.
Required Skills and Qualifications
- Education: Bachelor's or Master's degree in Electrical Engineering, Computer Science, Optical Engineering, Robotics, or a related technical discipline.
- Experience: Minimum 5+ years developing computer vision or industrial Automated Optical Inspection (AOI) systems.
- Programming & Libraries: Strong proficiency in C++ or Python, with hands-on experience using computer vision libraries such as OpenCV, Halcon, or Matrox Imaging Library (MIL).
- Deep Learning for Vision: Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) applied to image segmentation or defect classification.
- Optical Principles: Solid understanding of industrial optics, magnification, depth of field, telecentric lenses, and illumination techniques (brightfield, darkfield, coaxial).
- Hardware Interfacing: Experience interfacing with industrial camera standards (GigE Vision, Camera Link, USB, CoaXPress) and frame grabbers.
Preferred Qualifications
- Experience working directly with automated wafer probers (e.g., Tokyo Electron/TEL, Accretech, FormFactor).
- Knowledge of semiconductor wafer morphology, die layouts, and common physical defect types (scratches, contamination, probing marks).
- Familiarity with GPU acceleration tools such as NVIDIA CUDA or TensorRT for real-time inference optimization.
How To Apply:
Interested candidate, please submit your updated resume in MS WORD Format to Terry Ng, email – [Confidential Information]
EA Personnel Reg. No. R1107654, Achieve Career Consultant Pte Ltd EA Licence No. 05C3451
We regret that only shortlisted candidates will be notified. Thank you for your interest in this opportunity.
