Remote Video Annotation Jobs in Midlothian, VA (NOW HIRING)

As of Sep 4, 2026, the average yearly pay for remote video annotation in Midlothian, VA is $71,522.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,900.00 and $82,900.00 per year, depending on experience, location, and employer.

Remote video annotation is the process of labeling or tagging objects, actions, or events in video footage while working from a location outside of a traditional office, typically from home. Annotators use specialized software tools to draw boxes, create masks, or assign labels to specific frames or sequences in videos. This annotated data is essential for training and improving computer vision models used in applications like self-driving cars, security systems, and entertainment technology. Remote video annotation jobs offer flexibility, but often require attention to detail, strong computer skills, and the ability to follow detailed guidelines.

As a Remote Video Annotation specialist, your daily tasks typically include reviewing video footage, accurately labeling objects or actions according to specific guidelines, and ensuring data consistency for machine learning projects. One common challenge is maintaining high attention to detail over long periods, as precise annotations are crucial for training effective AI models. Additionally, you'll often collaborate with project managers or quality assurance teams to clarify requirements, discuss edge cases, and receive feedback. Flexibility and good time management are important, as workloads can vary based on project deadlines and client needs.

To excel as a Remote Video Annotation Specialist, you need strong attention to detail, visual accuracy, and basic computer literacy, often supported by prior experience in data labeling or related fields. Familiarity with annotation platforms (such as CVAT or Labelbox) and understanding of video formats and metadata are typically required. Effective time management, reliability, and clear communication help specialists meet deadlines and collaborate remotely. These skills ensure precise data labeling, which is crucial for training high-performing AI and machine learning models.