Computer Vision Engineer – Intelligent Inspection & Automation

LICO RESOURCES PTE. LTD.; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A precision automation firm in Singapore is seeking a Computer Vision Engineer to develop AI-based vision solutions for semiconductor production. The role involves advanced image processing and machine learning to enhance automated inspection and defect detection processes. Candidates should have a relevant degree and experience in computer vision and related tools, including Python and C++. Interested candidates should apply via email with a reference number.

Qualifications

• Solid experience in computer vision, image analysis, and applied machine learning.
• Proficiency in Python and C++ along with relevant libraries.
• Familiarity with building and optimizing vision algorithms for high-throughput or precision manufacturing.

Responsibilities

• Design and implement vision algorithms for automated inspection.
• Develop and deploy deep learning-based models for vision systems.
• Integrate vision software with robotics and automation platforms.
• Optimize system performance for detection accuracy and speed.

Skills

Computer vision

Image analysis

Applied machine learning

Python

C++

OpenCV

TensorFlow

PyTorch

Deep learning architectures

Problem-solving

Education

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

Tools

CUDA

FPGA

Job description

Lico Resources, a specialist in Cybersecurity & Tech GRC recruitment, is collaborating with a leading precision automation company that plays a critical role in the advancement of semiconductor manufacturing technologies. Known for their high-performance systems and engineering excellence, this organization drives innovation across complex inspection and assembly solutions.

This is an exciting opportunity for a technically driven Computer Vision Engineer to develop next-generation vision and AI solutions for semiconductor production. Based in Singapore, this role focuses on applying advanced image processing, machine learning, and real-time analysis to support defect detection, automated inspection, and process optimization in high-throughput environments.

Key Responsibilities

• Design and implement vision algorithms for automated inspection, feature detection, and pattern recognition in semiconductor backend processes.
• Develop and deploy deep learning-based models to enable high-speed, high-accuracy vision systems.
• Integrate vision software with robotics, automation platforms, and precision equipment such as die bonders and wire bonders.
• Apply advanced image processing techniques for tasks including object tracking, defect classification, and yield improvement.
• Collaborate with hardware, software, and process engineering teams to ensure seamless real-time integration across inspection systems.
• Analyze performance data, validate models, and fine-tune algorithms to meet production standards and operational requirements.
• Optimize system performance in terms of detection accuracy, processing speed, and operational reliability.
• Contribute to the continuous enhancement of vision frameworks to support scalability, robustness, and deployment readiness.

Qualifications

Essential:

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field.
• Solid experience in computer vision, image analysis, and applied machine learning.
• Proficiency in Python and C++, along with libraries such as OpenCV and frameworks like TensorFlow or PyTorch.
• Familiarity with building and optimizing vision algorithms for high-throughput or precision manufacturing applications.

Preferred:

• Experience with deep learning architectures such as CNNs, GANs, or Transformer-based models applied to vision tasks.
• Exposure to semiconductor automation systems or optical inspection tools.
• Knowledge of real-time processing techniques and hardware acceleration technologies (e.g., CUDA, FPGA).
• Strong problem-solving mindset and the ability to communicate technical concepts clearly across teams.

If you are interested in this role, please send us your updated resume today to [e-mail] quoting reference number A05548. Please note that only shortlisted candidates will be notified.

"Data provided is for recruitment purposes only."

Job Reference No: A05548
EA Licence No.: 13C6733
EA Registration No.: R1333454