AI Data Annotation Intern — Image & Video About the Role We're looking for a detail-driven intern to help produce and review the labelled image and video data that trains and fine-tunes AI models. You'll be one of the people in the loop who make AI systems accurate — turning raw footage into the structured, high-quality data models actually learn from. Job Responsibilities Apply precise labels — tags, timestamps, segment boundaries, and attribute flags — to image and video content, following detailed project guidelines Review and validate annotations for consistency and accuracy, including your own submissions and, as you grow in the role, other contributors' work Resolve ambiguous or edge-case data points using judgment grounded in the project's annotation guidelines — flag genuinely unclear cases to your reviewer rather than guessing Validate and correct AI-generated outputs as part of model fine-tuning workflows — flagging where a model's output is wrong, inconsistent, or low-confidence Work within annotation tools/platforms internal tool to complete and submit labelled batches against agreed targets Communicate with your reviewer or team lead to clarify guideline questions and incorporate feedback into future batches Maintain strict confidentiality of project data and any client information you're exposed to What You'll Need High attention to detail and consistency across repetitive, detail-sensitive work Ability to follow detailed, sometimes-evolving written instructions precisely Comfort with digital tools, structured data entry, and web-based platforms Clear written communication — for flagging issues and asking the right clarifying questions A personal computer or laptop with a stable internet connection No prior annotation or coding experience required — full guidelines and training provided Nice to Have Prior exposure to annotation tools such as CVAT, Labelbox, or Supervisely Basic familiarity with computer vision or machine learning concepts Prior data entry, QA, or research-assistant experience

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