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Specialized CV and edge deployment skills make this a niche role with lower applicant competition.
Computer vision expertise is highly domain-specific, reducing cross-industry transferability.
Mandatory deep learning, OpenCV, camera calibration, and deployment skills create high filtering requirements.
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Design, train, and optimize CNN-based models for classification, object detection, and segmentation using TensorFlow or PyTorch.
Develop and deploy image processing and computer vision algorithms including camera calibration and coordinate mapping for accurate measurement systems.
Collaborate with automation, hardware, and software teams to integrate computer vision models into production systems and continuously improve model performance.
B.Tech/BE in Computer Science, Electronics, Mechatronics, or related field.
Strong programming skills in Python and C++ with hands-on experience in TensorFlow and/or PyTorch.
Experience with CNN architectures (ResNet, VGG, MobileNet, YOLO, SSD, Faster R-CNN) and OpenCV-based image processing.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in implementing computer vision algorithms in real-world applications with demonstrated success.
Proficient in dataset preparation, annotation, augmentation, and deploying models on edge or industrial systems.
Comfortable working cross-functionally with automation, hardware, and software teams to integrate and optimize solutions at scale.