Data Annotation Specialist

Role Overview As a Data Annotator, you will be responsible for labeling and categorizing large datasets (text, image, video, and audio) to help train Machine Learning (ML) and Artificial Intelligence (AI) models. Your work ensures that AI systems—ranging from self-driving cars to chatbots—can understand and interact with the world accurately. Key Responsibilities Image & Video Tagging: Drawing bounding boxes, polygons, and keypoints on visual data to identify objects (e.g., pedestrians, traffic signs, medical anomalies). Text Annotation: Identifying named entities (NER), sentiment analysis, and intent classification for Natural Language Processing (NLP) models. Audio Transcription: Converting speech to text and labeling acoustic events for voice-recognition software. Quality Assurance: Reviewing and correcting existing labels to ensure 95%+ accuracy and consistency across datasets. Guideline Adherence: Strictly following project-specific instructions and providing feedback to engineers on edge cases or ambiguous data points. Required Skills & Qualifications Education: Bachelor’s degree in any field (Computer Science, Linguistics, or Statistics preferred but not mandatory). Attention to Detail: Ability to spot minute differences and patterns in data for hours at a time. Tech Savvy: Familiarity with annotation tools like CVAT, Labelbox, or Roboflow (training is often provided). Language Skills: Proficiency in English; knowledge of regional Indian languages is a significant plus for localized AI projects. Basic AI Knowledge: A general understanding of how data feeds into Machine Learning models.