Trainer/Educator: Basic Data Annotation

The Role

The Trainer will be responsible for delivering the Basic Data Annotation curriculum to students through classroom sessions, practical demonstrations, hands-on exercises, and project-based learning. The trainer will prepare learners for entry-level careers in AI data annotation.

Responsibilities:

• Train students in image, text, audio, and basic video annotation techniques, including image classification, tagging, bounding box annotation, text labeling, and audio classification.
• Conduct practical training on industry-standard annotation tools such as CVAT, Label Studio, and other relevant platforms, enabling students to build proficiency in real-world annotation workflows.
• Teach annotation standards, quality assurance (QA), data validation, productivity improvement techniques, ethical data handling, and privacy practices to ensure the creation of high-quality AI datasets.
• Design, administer, and evaluate assignments, practical exercises, assessments, and capstone projects, providing constructive feedback to enhance learner performance.

Qualification:

• Bachelor's degree in Computer Science, IT, AI, Data Science or related field.
• 1 to 3 years' experience in data annotation or AI data operations.
• Hands-on experience with data annotation tools such as CVAT, Label Studio, Labelbox, or similar platforms will be an added advantage.