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Remote Video Labelling information

What are the key skills and qualifications needed to thrive as a Remote Video Labelling Specialist, and why are they important?

To thrive as a Remote Video Labelling Specialist, attention to detail, basic computer proficiency, and a high school diploma or equivalent are generally required. Familiarity with annotation tools, video editing software, and data labeling platforms is typically expected, with some roles preferring experience in machine learning or data management systems. Strong time management, focus, and effective communication skills help individuals excel in independent, deadline-driven environments. These skills ensure accurate data labeling, which is crucial for training high-quality AI and machine learning models.

What are some common challenges faced by remote video labelling professionals, and how can they be managed?

Remote video labelling professionals often encounter challenges such as staying focused during repetitive tasks, ensuring accuracy when identifying subtle visual details, and managing communication with team members across different time zones. To address these, it's helpful to set up a distraction-free workspace, take regular breaks to maintain concentration, and use collaborative tools to stay connected with supervisors and peers. Additionally, following established labelling guidelines and participating in quality assurance sessions can help maintain consistency and accuracy in your work.

What is remote video labelling?

Remote video labelling is the process of watching video footage and accurately annotating or tagging objects, actions, or events within the video, all while working from a remote location, usually from home. This work is essential for training machine learning and AI models, particularly in fields like autonomous vehicles, security, and content moderation. Video labellers use specialized software to mark frames and provide metadata that helps computers understand visual information. Attention to detail and consistency are crucial in this job to ensure high-quality labelled data.

What is the difference between Remote Video Labelling vs Remote Image Annotation?

AspectRemote Video LabellingRemote Image Annotation
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAutonomous vehicles, surveillance, AI trainingObject detection, medical imaging, retail
Search & Comparison IntentUnderstanding differences in data labeling rolesUnderstanding differences in annotation tasks

Remote Video Labelling involves annotating video data frame-by-frame, often requiring temporal consistency, while Remote Image Annotation focuses on labeling individual images. Both roles are remote, require attention to detail, and are used in AI training across various industries. The main difference lies in the data type: videos versus images, with video labelling demanding more complex, time-sensitive annotations.

What are the most commonly searched types of Video Labelling jobs in Virginia? The most popular types of Video Labelling jobs in Virginia are:
What are popular job titles related to Remote Video Labelling jobs in Virginia? For Remote Video Labelling jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Remote Video Labelling jobs in Virginia look for? The top searched job categories for Remote Video Labelling jobs in Virginia are:
What cities in Virginia are hiring for Remote Video Labelling jobs? Cities in Virginia with the most Remote Video Labelling job openings:
Remote Video Labelling jobs near you

Remote Video Annotators

Barker Staffing Solutions LLC

Hampton, VA • Remote

Full-time

Posted 12 days ago

Job description

Location: Remote (U.S.-based preferred or strong familiarity with U.S. curriculum)
Type: 1099 Contract
Hours: Minimum 40 hours/week
Compensation: Competitive hourly rate based on experience and role

About the Role:

The client is a NYC-based non-profit with a social mission to lift economically and socially marginalized youth out of poverty in Asia and Africa. Using impact-based outsourcing, they create sustainable, living-wage jobs by providing data-labeling and annotation services for training datasets used in Computer Vision and GenAI applications.

The client is seeking dynamic, passionate, detail-oriented, and self-motivated individuals who enjoy providing annotation services. This position is ideal for self-starters with customer-facing etiquette, good communication skills, and a strong work ethic.

Position: Video Annotator (Traffic & Behavioral)
Responsibilities for the Retrieval Benchmark Annotation Project:
Perform multi-dimensional scene annotation for autonomous driving data. As an annotator, go beyond object labeling and perform structured classification, behavioral analysis, and apply causal reasoning.
Apply Advanced Annotation Capability by using the following skills:
Use your experience with annotation tools (segmentation, object tracking, timelines)
Apply complex taxonomies and attribute structures
Deploy accurate frame-level updates and lifecycle management of annotations
Scene Interpretation & Spatial Awareness by using the following skills:
Use your strong understanding of road environments and layouts
Identify road types, traffic infrastructure, and conditions
Demonstrate accurate perception of relative positioning and spatial relationships

Apply Behavioral & Causal Reasoning in the following tasks:
Interpret why events occur, not just what is visible
Identify relationships between ego vehicle, environment, and agents
Create logical links between entities

Apply Temporal Analysis with the following tasks:
Track changes over time within a scene
Update attributes dynamically as scenes evolve

Use Traffic Knowledge & Driving Judgment by using the following skills:
Strong understanding of traffic rules and right-of-way principles
Use discerning ability to assess legal vs illegal and safe vs aggressive behavior

Apply Multi-Agent Interaction Understanding when performing the following tasks:
Analyzing interactions between vehicles, pedestrians, objects, and the environment
Understanding and determining the influence and dependency between actors
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by federal, state, or local laws.

Why Join Us?

  • 100% remote, flexible work scheduled based on the client's needs

  • Be part of a collaborative, mission-driven project

  • Work with a team that values your educational expertise