TEAL- Computer Vision Engineer

• Design, train, and optimize CNN-based models for classification, object detection, and segmentation using TensorFlow or PyTorch
• Develop image processing algorithms using OpenCV for filtering, feature extraction, and measurement
• Perform camera calibration, lens distortion correction, and coordinate mapping for accurate measurement systems
• Prepare datasets, including labeling and augmentation, for training deep learning models
• Deploy trained models into production systems
• Collaborate with automation, hardware, and software teams for system integration
• Document calibration processes, models, datasets, and deployment workflows
• Conduct thorough analysis of model performance and fine-tune parameters to enhance accuracy and efficiency
• Implement cutting-edge computer vision techniques to improve object recognition and tracking capabilities
• Stay updated on the latest advancements in deep learning and image processing to continuously enhance project outcomes

B.Tech / BE in Computer Science, Electronics, Mechatronics, or related field

Strong programming skills in Python and C++

Hands-on experience with TensorFlow and/or PyTorch

Strong understanding of Convolutional Neural Networks (CNNs)

Experience with CNN architectures (ResNet, VGG, MobileNet, YOLO, SSD, Faster R-CNN)

Knowledge of object detection, image classification, and segmentation techniques

Strong experience with OpenCV and classical image processing

Experience in camera calibration techniques (intrinsic/extrinsic parameters, distortion correction)

Understanding of coordinate transformation and measurement systems

Knowledge of camera pipelines and real-time image acquisition

Experience with dataset preparation, annotation, and augmentation

Familiarity with deploying models on edge devices or industrial systems

Knowledge of GPU acceleration (CUDA) is an added advantage

Strong debugging, optimization, and analytical problem-solving skills

Additionally, the ideal candidate should have a proven track record of successfully implementing computer vision algorithms in real-world applications. Proficiency in developing and optimizing deep learning models for image processing tasks is highly desirable. Experience in working with large-scale datasets and understanding of data preprocessing techniques would be a plus. Strong communication skills and the ability to work collaboratively in a team environment are essential for this role.