Professions that train AI for deep learning usually involve multiple roles, among which the "AI corpus annotator" is directly related to data annotation work. They are responsible for cleaning, labeling, and classifying large amounts of data that are used to train deep learning models to help them understand and recognize patterns.
In addition to this, and more broadly, there are several professions that are also directly involved in or responsible for the process of training AI deep learning:
1.Data scientists: They design and implement machine learning projects, including preparing datasets, building deep learning models, and optimizing model performance.
2.Machine Learning Engineer: Focuses on developing and deploying algorithms and systems capable of deep learning, including training, parameter tuning, and integration of models into products or services.
3.AI Researcher Scientist: Engage in cutting-edge AI research in academia or industry, and develop new deep learning technologies and architectures.
4.Deep learning engineers: Particular attention is paid to the design, training, and application of deep neural networks, which may involve multiple fields such as computer vision and natural language processing.