Computer Vision Engineer

Model development and deployment involve designing, training, optimizing, and deploying computer vision models for tasks such as detection, classification, segmentation, and tracking, with ongoing improvements for accuracy and performance. Image and video processing focus on analyzing visual data, applying preprocessing techniques, and handling real-time and batch workflows. Data annotation and evaluation include preparing labeled datasets, assessing model performance, and improving data quality, while optimization and troubleshooting ensure efficient operation by enhancing speed, resolving pipeline issues, and monitoring deployed models.

• Qualification : Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Skills : Core computer vision skills include experience with OpenCV, NumPy, image processing, deep learning frameworks like PyTorch or TensorFlow (PyTorch preferred), and object detection and segmentation models. Machine learning skills cover neural networks, training and evaluation processes, handling large image and video datasets, and data augmentation. General skills include strong Python programming, basic cloud and GPU knowledge, and strong analytical and problem-solving abilities.
• Experience : Minimum 1 years.