Data Annotator

Job Summary - To train AI, large language model. **Job description**: A **data annotator** refers to someone or something that labels or tags raw data (such as text, images, or audio) to make it usable for machine learning models. The goal of data annotation is to provide the machine learning algorithm with labeled examples that it can learn from in order to make predictions or classifications on unseen data. In the context of machine learning and AI, **data annotation** can be used in several domains, such as: - **Text Annotation**: - **Named Entity Recognition (NER)**: Labeling names, places, dates, etc., in a piece of text. - **Sentiment Analysis**: Labeling whether a text (e.g., a tweet or a review) is positive, negative, or neutral. - **Part-of-Speech Tagging**: Labeling each word in a sentence with its corresponding part of speech (e.g., noun, verb, adjective). - **Image Annotation**: - **Object Detection**: Labeling objects in images with bounding boxes or segmentation masks (e.g., identifying cars, people, animals). - **Image Classification**: Labeling an image with a class, such as "dog," "cat," "car," etc. - **Semantic Segmentation**: Labeling each pixel in an image to assign it a class (e.g., ground, sky, building). - **Audio Annotation**: - **Speech-to-Text**: Converting spoken words into written text. - **Sound Classification**: Labeling different sounds (e.g., dog bark, car horn) in an audio clip. - **Speaker Identification**: Labeling different speakers in a conversation. - **Video Annotation**: - **Action Recognition**: Labeling actions or activities (e.g., walking, jumping, running) in video frames. - **Object Tracking**: Tracking the movement of objects across video frames. **Job Types**: Full-time, Contract Contract length: 12 months Pay: Up to E£57,241.00 per month