Senior Vision Design Engineer

aac technologies pte. ltd.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

AAC Technologies Pte. Ltd. in Singapore seeks an experienced engineer to design and develop computer vision and AOI software for wafer inspection in high-volume manufacturing.

You will implement defect detection, die alignment, and classification algorithms using C++/Python with OpenCV/HALCON/MIL and GPUs for acceleration. Prior semiconductor experience is a plus.

Qualifications

• Bachelor's or Master's degree in Electrical Engineering, Computer Science, Optical Engineering, Robotics, or related discipline.
• Minimum 5 years in computer vision, machine vision, or AOI system development, preferably in semiconductor/industrial automation.
• Strong programming in C++ or Python with OpenCV, HALCON, or MIL.
• Experience with deep learning frameworks such as PyTorch or TensorFlow for image analysis and defect classification.
• Good understanding of industrial optics, imaging systems, calibration, and illumination.
• Experience integrating cameras and vision hardware using GigE Vision, Camera Link, USB3 Vision, CoaXPress, etc.
• Knowledge of wafer inspection, wafer probers, GPU acceleration (CUDA, TensorRT) is a plus.

Responsibilities

• Design and develop computer vision, image processing, and deep learning algorithms for wafer inspection and defect detection.
• Integrate and optimize optical systems, including cameras, lenses, lighting, and vision hardware.
• Develop automated calibration and alignment solutions for high-precision wafer inspection.
• Build and optimize real-time vision software; integrate with wafer probers and automation equipment.
• Improve image acquisition and processing for high-speed, high-volume manufacturing.
• Evaluate inspection accuracy via testing, validation, and statistical analysis.
• Prepare and maintain BOM and engineering documentation.

Skills

Computer vision

Machine vision

AOI systems

C++

Python

OpenCV

Deep learning

TensorRT

CUDA

Camera calibration

Industrial optics

GigE Vision

Camera Link

CoaXPress

Education

Bachelor's or Master's Degree in Electrical Engineering, Computer Science, Optical Engineering, Robotics

Tools

OpenCV

HALCON

MIL (Matrox Imaging Library)

Job description

Key Responsibilities

• Design and develop computer vision, image processing, and deep learning algorithms for wafer inspection, defect detection, classification, and die alignment.
• Integrate and optimize optical systems, including industrial cameras, lenses, lighting, filters, and vision hardware.
• Develop automated calibration and alignment solutions to achieve high‑precision wafer inspection.
• Build and optimize real‑time vision software and integrate vision systems with wafer probers and automation equipment.
• Improve image acquisition and processing performance for high-speed, high-volume manufacturing environments.
• Evaluate and optimize inspection accuracy through testing, validation, and statistical performance analysis.
• Prepare and maintain Bill of Materials (BOM) and support engineering documentation.

Requirements

• Bachelor's or Master's Degree in Electrical Engineering, Computer Science, Optical Engineering, Robotics, or a related discipline.
• At least 5 years of experience in computer vision, machine vision, or Automated Optical Inspection (AOI) system development, preferably within the semiconductor or industrial automation industry.
• Strong programming skills in C++ or Python, with hands‑on experience using computer vision libraries such as OpenCV, Halcon, or Matrox Imaging Library (MIL).
• Experience with deep learning frameworks such as PyTorch or TensorFlow for image analysis and defect classification.
• Good understanding of industrial optics, imaging systems, camera calibration, and illumination techniques.
• Experience integrating industrial cameras and vision hardware using GigE Vision, Camera Link, USB3 Vision, CoaXPress, or similar interfaces.
• Knowledge of semiconductor wafer inspection, wafer probers, GPU acceleration (CUDA, TensorRT), or related technologies is an advantage.