Vision Engineer

Adecco Personnel Pte Ltd.; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

A leading Semiconductor organisation in Singapore is seeking a Computer Vision Engineer to design advanced vision solutions for semiconductor manufacturing. The role involves algorithm development, deep learning integration, and collaboration with engineering teams to enhance product quality and efficiency. Ideal candidates will have a relevant degree and expertise in computer vision and machine learning. Interested applicants should send their resume and salary expectations to our hiring team.

Qualifications

• 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.
• Familiarity with semiconductor automation, optical inspection, or metrology is advantageous.
• Knowledge of real-time processing, embedded systems, and hardware acceleration (CUDA, FPGA, etc.) is a plus.
• Strong analytical, problem-solving, and communication skills.

Responsibilities

• Design, develop, and optimize computer vision algorithms for defect detection.
• Implement and deploy deep learning-based vision models for inspection processes.
• Integrate vision systems with robotics and automation platforms.
• Develop techniques for pattern recognition and quality inspection.
• Collaborate with engineering and production teams to enhance vision inspection.
• Conduct data analysis and performance tuning for optimal system performance.

Skills

Computer vision

Image processing

Machine learning

Python

C++

Deep learning

OpenCV

TensorFlow

PyTorch

Education

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Robotics

Tools

OpenCV

TensorFlow

PyTorch

Job description

An exciting new opportunity to work with the R&D team of a leading Semiconductor organisation.

About the Role

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.

Key Responsibilities

• 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.

Interest & Application

Prepare your updated resume (please include your current salary package with full breakdown such as base, incentives, annual wage supplement, etc.) and expected package and email to [e-mail]. We’d love to hear from you!