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Video Labelling Jobs (NOW HIRING)

Figure

Data Labeler

San Jose, CA · On-site

Responsibilities : • Use proprietary annotation tools to label objects, poses, and interactions in images and video streams from our humanoid robots • Collaborate with ML engineers to refine ...

Online Labels

Label Inspector

Sanford, FL · On-site

$15/hr

Watch this video to learn more about what we do here at Consolidated Label Overview: The Label Inspector is a great entry level position to learn about the print industry in a warehouse setting! You ...

micro1

Data-Video Generalist (Europe-based)

Follow detailed technical protocols to ensure all submissions meet strict quality, labeling, and determinism standards. * Consistently contribute a minimum of 10 hours of approved video data per week ...

Micro1

Data-Video Generalist (Europe-based)

Follow detailed technical protocols to ensure all submissions meet strict quality, labeling, and determinism standards. * Consistently contribute a minimum of 10 hours of approved video data per week ...

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How much do video labelling jobs pay per hour?

As of Aug 26, 2026, the average hourly pay for video labelling in the United States is $25.43, according to ZipRecruiter salary data. Most workers in this role earn between $19.23 and $29.09 per hour, depending on experience, location, and employer.

What is a video labelling?

A Video Labelling job involves annotating or tagging objects, actions, or events in video footage to train machine learning models. This process helps AI systems recognize and interpret visual data accurately. Tasks may include drawing bounding boxes, classifying scenes, or adding timestamps for specific events. Video labelling is commonly used in industries like autonomous driving, security surveillance, and content moderation.

What does a video labelling do?

A typical day in Video Labelling involves reviewing video footage, identifying and annotating specific objects or events according to project guidelines, and entering this data into specialized software tools. Team members often collaborate with data scientists, engineers, or quality assurance leads to ensure accuracy and consistency in the annotations. Depending on the project and employer, you may work independently or as part of a larger team, sometimes with set quotas or deadlines. This work is crucial for developing and refining AI and machine learning models, making attention to detail and adherence to standards especially important. Over time, experienced video labelling professionals may progress to quality assurance roles or team leads overseeing larger annotation projects.

What are the key skills and qualifications needed to thrive in video labelling, and why are they important?

To thrive as a Video Labelling professional, you should have excellent attention to detail, basic computer proficiency, and familiarity with visual content analysis. Knowledge of annotation platforms, video editing software, or AI training tools is often required, and experience with data labelling systems can be beneficial. Strong communication, reliability, and the ability to follow detailed guidelines are important soft skills for this role. These abilities ensure high-quality, consistent data annotation that directly supports machine learning and computer vision projects.

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Video Labelling jobs near you
Infographic showing various Video Labelling job openings in the United States as of August 2026, with employment types broken down into 92% Full Time, and 8% Contract. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $52,887 per year, or $25.4 per hour.

Data Labeler

San Jose, CA • On-site

Figure
See more jobs at Figureexternal

Full-time

Re-posted 11 days ago

Job description

Job Summary:
Figure is an AI Robotics company developing a general purpose humanoid. They are seeking a Data Labeler to help annotate and label data for AI training applications.
Responsibilities:
• Use proprietary annotation tools to label objects, poses, and interactions in images and video streams from our humanoid robots
• Collaborate with ML engineers to refine labeling guidelines and improve interface efficiency
• Identify and flag ambiguous or edge-case scenarios for review by the ML team
• Maintain high throughput and consistent quality across large annotation batches
• Contribute feedback on workflow improvements and tool enhancements
Qualifications:
Required:
• Strong attention to detail and the ability to apply consistent logic across diverse scenarios
• Comfortable navigating computer-based tools and quickly learning new software
• Patient, quality-focused mindset with the ability to juggle multiple assignments
• Clear written and verbal communication skills
• Reliable, self-motivated work style and a collaborative spirit within a fast-paced environment
• Fluency in English required
Company:
Figure is an AI robotics company that develops autonomous general-purpose humanoid robots. Founded in 2022, the company is headquartered in San Jose, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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