Software Development Engineer (Senior/Staff) | TT Vision Technologies Sdn Bhd · Teeming.ai
TT Vision Technologies Sdn Bhd
TT Vision Holdings Berhad is a technology-driven company established in 2001, specializing in the development and manufacturing of automated machine vision solutions. They offer cost-effective,…
TT Vision Holdings Berhad is a technology-driven company established in 2001, specializing in the development and manufacturing of automated machine vision solutions. They offer cost-effective,…
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Computer Vision, AI, or related fields.
Strong experience in machine vision, AOI systems, or industrial automation software development.
Solid understanding of classical computer vision and image processing techniques.
Experience with machine vision libraries such as HALCON, OpenCV, VisionPro, or equivalent platforms.
Experience in machine learning and deep learning frameworks such as PyTorch, TensorFlow, ONNX, or OpenVINO.
Strong programming skills in C#, C++, Python, or equivalent languages.
Experience in multithreaded software design, real-time processing, and performance optimization.
Familiarity with industrial hardware integration including cameras, lighting systems, motion controllers, and communication interfaces.
Strong analytical, debugging, and problem-solving skills in production manufacturing environments.
Experience in semiconductor, electronics, precision manufacturing, or industrial inspection systems is highly preferred.
Familiarity with GPU acceleration, CUDA, edge AI deployment, or high-performance computing is an advantage.
Strong teamwork, communication and technical leadership capability with ability to work across multidisciplinary engineering teams.
Descriptions of job duties:
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Develop and optimize computer vision algorithms for image inspection, defect detection, measurement, alignment, and classification applications.
Research, design, and implement machine learning and deep learning models for automated defect recognition, anomaly detection, and image analysis.
Analyse and evaluate image quality characteristics including focus, contrast, illumination uniformity, noise, distortion, and signal stability to improve inspection robustness and accuracy.
Lead technical investigations, root cause analysis, and algorithm optimization activities to improve inspection stability, reduce false rejects and escape defects, and achieve target performance for detection accuracy and throughput.
Design and develop high-speed real-time image processing pipelines including preprocessing, feature extraction, segmentation, pattern matching, and classification using multithreading, parallel computing, GPU acceleration, and performance optimization techniques.
Collaborate with hardware, optics, lighting, and process engineering teams to develop and integrate software solutions with industrial components such as cameras, frame grabbers, motion systems, PLCs, lighting controllers, and sensors to optimize imaging conditions and inspection performance.
Evaluate and benchmark classical vision methods versus AI/deep learning approaches for different inspection use cases and production conditions.
Build and maintain datasets, annotation workflows, validation methodologies, and model evaluation processes for AI-based inspection systems.
Support deployment, debugging, troubleshooting, and continuous improvement activities in production environments.
Review software design, algorithm implementation, and code quality to ensure maintainability, scalability, and engineering best practices.
Mentor and guide software and vision engineers in algorithm development.
Collaborate with cross-functional teams including software, process, electrical, mechanical, evaluation, and manufacturing teams to deliver integrated AOI solutions.
Research and evaluate emerging technologies in computer vision, AI, deep learning, and intelligent inspection systems for future platform enhancement.
Maintain technical documentation including algorithm specifications, validation reports, troubleshooting guides, and user manuals.
Drive continuous improvement initiatives for inspection capability, reliability, maintainability, and production efficiency.
