Video Annotator

Location: Fully Remote Schedule: Full-Time, Remote

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About The Role

We are looking for detail-oriented Video Annotators to support a Vision-Language-Action (VLA) dataset project. In this role, you will watch short video clips of physical tasks/activities and produce event-level annotations by segmenting each video into meaningful steps and writing clear, precise natural-language instructions describing the action taking place in each segment.

Key Responsibilities

• Watch assigned videos in full before beginning annotation to understand the overall task and context.
• Segment each video into discrete, logical steps/events based on visible action boundaries.
• Write clear, concise, and grammatically correct step-by-step descriptions for each segment, accurately reflecting what is happening on screen.
• Ensure annotations are action-oriented, unambiguous, and consistent in tense, tone, and phrasing across the dataset.
• Assign accurate start and end timestamps for each segment.
• Follow annotation guidelines, taxonomies, and style guides provided by the project team.
• Flag videos that are unclear, corrupted, mislabeled, or otherwise unsuitable for annotation.
• Participate in calibration sessions and incorporate reviewer/QA feedback to improve annotation quality and consistency.
• Meet daily/weekly productivity and quality targets without compromising accuracy.
• Maintain confidentiality of all project data and materials.

Required Qualifications

• English Proficiency: C1 level (CEFR) or above — strong command of grammar, vocabulary, and sentence construction is essential.
• Excellent attention to detail and ability to spot subtle changes in visual scenes.
• Strong written communication skills; ability to describe actions concisely and precisely.
• Comfort working with video-based tools and annotation software (training provided).
• Ability to work independently, follow detailed guidelines, and maintain consistency over repetitive tasks.
• Reliable internet connection and access to a computer with a modern browser.
• Basic computer literacy (file handling, web-based tools, spreadsheets).

Preferred Qualifications

• Prior experience in data annotation, labeling, transcription, or content moderation.
• Familiarity with AI/ML concepts, especially computer vision, NLP, or robotics datasets.
• Experience writing instructional or procedural content (how-to guides, SOPs, recipes).
• Exposure to annotation platforms (e.g., CVAT, Label Studio, Scale, or similar tools).

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