Job Description:
We are seeking a highly motivated and skilled Computer Vision Engineer to join our technology team and develop cutting-edge vision-based systems that bridge real-world visuals with intelligent computational analysis. The ideal candidate will have strong expertise in image processing, deep learning, and visual recognition technologies, and will play a key role in building intelligent systems that can interpret, analyze, and act upon visual data in real time.
As a Computer Vision Engineer, you will work closely with data scientists, AI researchers, and software engineers to design and implement vision algorithms for object detection, classification, tracking, segmentation, and recognition. You will leverage modern deep learning frameworks and architectures to develop scalable models optimized for both edge and cloud deployment. Your work will power applications across diverse domains such as industrial automation, smart surveillance, healthcare imaging, robotics, and quality inspection.
The role requires a solid understanding of machine learning principles, mathematical modeling, and image data pipelines — combined with the creativity to solve complex real-world problems through visual intelligence. This is a high-impact position that contributes directly to product innovation and data-driven automation in the era of Industry 4.0.
Responsibilities
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Develop and implement computer vision algorithms for image and video analysis.
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Design and train deep learning models for object detection, segmentation, classification, and tracking.
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Work with datasets to perform preprocessing, augmentation, and annotation management.
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Optimize vision models for performance and real-time inference on edge o
Responsibilities:
-
Develop and implement computer vision algorithms for image and video analysis.
-
Design and train deep learning models for object detection, segmentation, classification, and tracking.
-
Work with datasets to perform preprocessing, augmentation, and annotation management.
-
Optimize vision models for performance and real-time inference on edge or embedded systems.
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Integrate vision algorithms into production-grade software and hardware environments.
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Collaborate with cross-functional teams to align vision solutions with project goals.
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Conduct performance evaluations, error analysis, and continuous model improvements.
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Research and experiment with emerging vision architectures and techniques (CNNs, Transformers, 3D vision, etc.).
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Maintain proper documentation, dataset versioning, and model deployment pipelines.
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Contribute to innovations in visual analytics, automation, and intelligent decision systems.
Preferred Qualifications:
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Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or a related field.
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Strong experience with Python and libraries such as OpenCV, NumPy, TensorFlow, PyTorch, or Keras.
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Solid understanding of deep learning architectures (CNNs, RNNs, YOLO, Mask R-CNN, Vision Transformers, etc.).
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Experience with image and video data preprocessing, augmentation, and annotation tools.
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Familiarity with computer vision deployment on embedded or edge platforms (Jetson, Raspberry Pi, etc.).
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Understanding of mathematics and statistics behind image processing and feature extraction.
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Knowledge of MLOps practices, including model optimization and deployment pipelines.
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Experience with GPU acceleration, CUDA, or ONNX for performance tuning.
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Strong problem-solving, analytical, and debugging skills.
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Excellent teamwork, communication, and documentation abilities.