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Video Labelling Jobs in California (NOW HIRING)

Hooglee

Video Data Annotator - Contract

San Francisco, CA · On-site

$25/hr

Label and evaluate video content with high accuracy * Provide feedback on video quality and questionnaire setup to the AI Team * Communicate clearly about edge cases, inconsistencies, or improvements ...

Sciforium

LLM Dataset Engineer

San Francisco, CA · On-site

Familiarity with large-scale crawling of multimodal data and the associated challenges of video processing, codecs, and compression. • Taxonomy Design: Experience in designing complex labeling ...

Sciforium

LLM Dataset Engineer

San Francisco, CA · On-site

$155K - $210K/yr

Familiarity with large-scale crawling of multimodal data and the associated challenges of video processing, codecs, and compression. * Taxonomy Design: Experience in designing complex labeling ...

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Video Labelling information

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.

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 are the most commonly searched types of Video Labelling jobs in California? The most popular types of Video Labelling jobs in California are:
What are popular job titles related to Video Labelling jobs in California? For Video Labelling jobs in California, the most frequently searched job titles are:
What job categories do people searching Video Labelling jobs in California look for? The top searched job categories for Video Labelling jobs in California are:
What cities in California are hiring for Video Labelling jobs? Cities in California with the most Video Labelling job openings:
Video Labelling jobs near you
Infographic showing various Video Labelling job openings in California as of July 2026, with employment types broken down into 81% Full Time, 15% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Data Annotation Specialist - Computer Vision & Video Labeling

Wealth Recruitment, LLC

San Francisco, CA • On-site

$20 - $40/hr

Contractor

Re-posted 23 days ago

Job description

Are you highly detail-oriented with the ability to stay focused through complex visual tasks? We're seeking a Data Annotation Specialist to support cutting-edge computer vision and autonomous systems development by labeling and reviewing large-scale image and video datasets. In this role, your work will directly improve the quality of machine learning models used in advanced perception systems.

This is an excellent opportunity for candidates with experience in computer vision annotation, robotics, aviation, maritime operations, drone systems, military intelligence analysis, or sensor-based technologies who enjoy analytical, high-focus work in a fast-paced technical environment.

As a Data Annotation Specialist, you will:
  • Perform high-volume image and video labeling using internal proprietary annotation tools
  • Review visual datasets across multiple sensor and data types
  • Identify, document, and flag model failure cases to support machine learning improvements
  • Maintain strong labeling accuracy while meeting throughput and productivity targets
  • Track progress across large datasets and ensure consistent performance
  • Follow established annotation guidelines and escalate unclear or edge-case scenarios when needed
  • Work closely with technical teams to support rapid model development cycles

Requirements

Ideal Background

We're especially interested in candidates with backgrounds in:

  • Maritime operations
  • Drone/UAS operations
  • Aviation or aircraft systems
  • Military intelligence, ISR, or sensor analysis
  • Robotics or autonomous systems
  • Computer vision or video annotation environments
Required Qualifications
  • Must be a U.S. Citizen (required for CUI eligibility)
  • Experience with computer vision labeling, robotics annotation, or video/image analysis
  • Strong attention to detail and ability to maintain focus during repetitive visual review tasks
  • Comfortable working in proprietary internal software platforms
  • Ability to consistently balance speed and accuracy in a production environment
  • Strong pattern recognition and analytical skills
  • Reliable internet connection and ability to work independently

Benefits

Schedule
  • 20-30 hours per week initially while current project backlog is addressed
  • Hours may adjust based on project needs and performance

Pay Rate = $20 - $40 per hour

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