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Remote Video Labelling Jobs in Utah (NOW HIRING)

micro1 AI

First-Person AI Video Trainer

West Jordan, UT · Remote

$13/hr

Remote - experts based in Alabama, Arkansas, Georgia, Idaho, Indiana, Iowa, Kansas, Kentucky ... Follow detailed technical protocols to ensure all submissions meet strict quality, labeling, and ...

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Remote Video Labelling information

How much are data labelers paid?

Data labelers, including those working remotely in video labeling roles, typically earn between $10 and $20 per hour depending on experience, complexity of tasks, and the company. Pay rates can vary based on the platform, project scope, and whether the work is freelance or full-time employment.

How can I make 2000 a week working from home?

Remote video labelling jobs can pay varying rates, often between $10 and $20 per hour, depending on the company and project complexity. To earn $2,000 weekly, you would need to work approximately 100 hours at these rates, which may require high-volume or premium projects, strong attention to detail, and efficient use of annotation tools. Building experience and a good reputation can help access higher-paying opportunities in this field.

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 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.

Is data labeling work from home?

Remote video labelling jobs are often performed from home, allowing workers to complete tasks using a computer and internet connection. These roles typically require attention to detail, familiarity with labeling tools, and a flexible schedule, making them suitable for remote work environments.

What is a video labeling job?

A video labeling job involves reviewing and annotating video content to help train machine learning algorithms. Workers typically use specialized tools to add tags, identify objects, or categorize scenes, often working remotely with flexible schedules. Accuracy and attention to detail are important for this type of data annotation work.

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 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 popular job titles related to Remote Video Labelling jobs in Utah? For Remote Video Labelling jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Remote Video Labelling jobs in Utah look for? The top searched job categories for Remote Video Labelling jobs in Utah are:
What cities in Utah are hiring for Remote Video Labelling jobs? Cities in Utah with the most Remote Video Labelling job openings:
Remote Video Labelling jobs near you
Subject Matter Expert - Video & Motion Analytics

Subject Matter Expert - Video & Motion Analytics

micro1 AI

Salt Lake City, UT • Remote

$13/hr

Part-time

Posted 15 days ago

Job description

Job Title: Data-Video Generalist


Job Type: Contractor


Location: Remote - experts based in Alabama, Arkansas, Georgia, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Mississippi, Montana, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Utah, Virginia, West Virginia, and Wisconsin.


Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Key Responsibilities:

  1. Capture precise motion data using your smartphone during specified physical tasks.
  2. Supported devices include the iPhone 12 and later, Google Pixel 6 and later, and Samsung Galaxy S21 and later.
  3. Record synchronized video footage to validate and enhance the integrity of collected sensor data.
  4. Follow detailed technical protocols to ensure all submissions meet strict quality, labeling, and determinism standards.
  5. Consistently contribute a minimum of 10 hours of approved video data per week throughout the project duration.
  6. Communicate effectively with the team to clarify guidelines and provide feedback on data collection processes.
  7. Ensure timely and reliable delivery of data outputs in accordance with project milestones.
  8. Participate in required device compatibility checks and a custom AI-enabled interview process.


Required Skills and Qualifications:

  1. Access to a head strap to be able to record both hands within 48 hours of the start date.
  2. Demonstrated adherence to standardized protocols and rigorous technical instructions.
  3. Proven ability to manage and deliver reliable output in a fast-paced, data-driven environment.
  4. Strong written and verbal communication skills; ability to document work and collaborate remotely.
  5. Experience with mobile devices and a high level of digital literacy.
  6. Physical capability to perform repetitive movement tasks safely and accurately.
  7. Access to a compatible smartphone for high-fidelity sensor and video data collection.
  8. Eligibility to work in designated U.S. states.
  9. Note: Applications submitted with a Gmail address are strongly preferred for seamless tool integration.


Compensation Structure

Compensation is output-based; experts are paid per recorded video that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow.


Start Timeline & Availability

We typically fill roles within 48 hours, so we’re looking for teammates who are ready to jump in. If selected, we’d love for you to start your first task as soon as you move forward with your application. The expectation is to begin within ~24 hours of completing onboarding.


Equipment Requirements

Mobile:

Tasks for this project must be performed from a mobile device (smartphone). Experts will record their workflow directly from the mobile device while completing tasks.


Head Strap / Wearable: Tasks for this project must be performed using a head-mounted camera (head strap setup). Experts will record first-person video of physical tasks. The required head strap and any accompanying equipment specifications will be shared during onboarding.

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