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Video Labelling Jobs in Montreal, QC (NOW HIRING)

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Video Labelling information

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.

What are popular job titles related to Video Labelling jobs in Montreal, QC?

For Video Labelling jobs in Montreal, QC, the most frequently searched job titles are:

What job categories do people searching Video Labelling jobs in Montreal, QC look for?

The top searched job categories for Video Labelling jobs in Montreal, QC are:

Infographic showing various Video Labelling job openings in Montreal, QC as of August 2026, with employment types broken down into 93% Full Time, and 7% Contract. Highlights an 91% In-person, and 9% Remote job distribution.

Data Labeling Specialist: Remote Contract

Workada

Mascouche, QC • Remote

Full-time

Posted 26 days ago


Job description

At Workada, we're not just labeling data, we're helping improve the technology people use every day. Our work creates the examples and feedback that make advanced systems more accurate, consistent, and useful.

What You'll Do

Evaluate outputs from AI models, text, images, video, and documents against detailed criteria. Assess quality, spot errors and inconsistencies, and write clear, well-reasoned justifications for your judgments. Every evaluation you complete helps these systems perform better in the real world.

Who We're Looking For

People who write clearly, think critically, and can back up a judgment call with a clear explanation. This role suits people who've done work built around precise written evaluation, UI/UX design, graphic design, photography, video production, editorial or research work, or writing technical specs and requirements.

  • Strong readers and writers with sound judgment
  • Comfortable evaluating creative or technical work against a set of criteria
  • Takes quality seriously and catches what others miss
  • Can follow detailed written guidelines independently
  • Qualifications

    Technical Requirements

    What We Offer

  • Remote, flexible contract work
  • Clear guidelines and training
  • Performance feedback and opportunities to grow
  • A mission-driven team focused on accuracy and quality
  • undefined