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Data Labeling Jobs in Ontario (NOW HIRING)

Mercor

Video Data Reviewer - Egocentric

Toronto, ON · Remote

CA$20 - CA$25/hr

Experience with video annotation, data labeling, computer vision datasets, or egocentric video. Start Date * Monday morning 17th August (PST) Application Process (Takes 20-30 mins to complete)

Mercor

Video Data Reviewer - Egocentric

Toronto, ON · Remote

CA$20 - CA$25/hr

Experience with video annotation, data labeling, computer vision datasets, or egocentric video. Start Date * Monday morning 17th August (PST) Application Process (Takes 20-30 mins to complete)

LXT

Korean - Data Entry Clerk (Transcriber)

Mississauga, ON · On-site

CA$22 - CA$29/hr

Data classification and data labeling according to defined criteria * Ability to meet deadlines and daily KPIs * Availability to work up to full-time hours at LXT's secure facility in Mississauga or ...

LXT

Korean - Data Entry Clerk (Transcriber)

Mississauga, ON · On-site

CA$22 - CA$29/hr

Data classification and data labeling according to defined criteria * Ability to meet deadlines and daily KPIs * Availability to work up to full-time hours at LXT's secure facility in Mississauga or ...

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Data Labeling information

What is data labeling?

A Data Labeling job involves annotating or tagging data, such as images, text, audio, or videos, to help train machine learning models. Labelers follow specific guidelines to classify data accurately so that AI systems can learn patterns and make predictions. This role is essential in fields like computer vision, natural language processing, and speech recognition. Strong attention to detail and consistency are crucial for ensuring high-quality training datasets.

What are the typical day-to-day responsibilities of a data labeling professional?

A Data Labeling professional is primarily responsible for reviewing and accurately tagging images, text, audio, or video data according to specified guidelines. Daily tasks often include managing large datasets, using annotation software to classify data, and verifying the quality and accuracy of the labels. Collaboration with data scientists, project managers, and other annotators is common, especially when clarifying labeling guidelines or resolving ambiguities. Attention to detail is crucial, as high-quality labeled data directly impacts the effectiveness of machine learning models and AI applications. Most positions are structured in team environments, where productivity and communication skills help ensure project deadlines are met.

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

To thrive in Data Labeling, you need meticulous attention to detail, strong analytical abilities, and basic computer literacy, often supported by a high school diploma or equivalent. Familiarity with data annotation tools, image or text editing software, and experience with platforms like Labelbox or Amazon SageMaker Ground Truth are commonly advantageous. Exceptional concentration, patience, and the ability to follow precise instructions are valuable soft skills in this position. These skills and qualities are essential for ensuring the accuracy and consistency of labeled datasets, which are critical for training reliable AI and machine learning models.

How can I get started in data labeling?

To get started in data labeling, you should develop basic skills in data annotation tools and understand labeling guidelines for different data types such as images, text, or audio. Many entry-level positions require attention to detail and sometimes a background in relevant fields like computer science or linguistics; online courses and practice datasets can help build your skills. Additionally, creating a strong profile on job platforms and applying to companies that offer remote or flexible data labeling roles can increase your chances of starting in this field.

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the platform or employer. Some may work as freelancers or part-time, with pay rates varying accordingly.

Is data labeling a good career?

Data labeling is a growing field that involves annotating data for machine learning models, often requiring attention to detail and familiarity with tools like labeling platforms. It can offer flexible schedules and entry-level opportunities, but typically provides lower pay compared to other tech roles and may lack long-term career advancement without additional skills. Overall, it can be a suitable starting point for those interested in AI and data science, but may not be ideal as a long-term career without further development.

What are data labeling jobs?

Data labeling jobs involve annotating or tagging data such as images, text, or videos to help train machine learning models. These roles typically require attention to detail and familiarity with labeling tools or software, and may be performed remotely or in a team environment.

What are the most commonly searched types of Data Labeling jobs in Ontario?

The most popular types of Data Labeling jobs in Ontario are:

What are popular job titles related to Data Labeling jobs in Ontario?

For Data Labeling jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Data Labeling jobs in Ontario look for?

The top searched job categories for Data Labeling jobs in Ontario are:

Data Labeling jobs near you
Infographic showing various Data Labeling job openings in Ontario as of August 2026, with employment types broken down into 72% Full Time, 9% Part Time, 7% Temporary, and 12% Contract. Highlights an 86% In-person, and 14% Remote job distribution.

Video Data Reviewer - Egocentric

Mercor

Toronto, ON • Remote

CA$20 - CA$25/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: AI Data Generalist — Egocentric Video Review
Type: Contract
Compensation: $20–$25/hour
Location: Remote
Duration: Approximately 2 weeks

Role Responsibilities

  • Review egocentric video data and complete structured quality-review tasks.
  • Evaluate action segments within videos for accurate start and end boundaries.
  • Adjust or flag incorrect boundaries according to guidelines.
  • Maintain consistent judgment across a high volume of short action segments.
  • Complete assigned videos within the project timeline.

Qualifications

Must-Have

  • Excellent attention to detail and visual comprehension.
  • Ability to distinguish closely related actions and moments in video.
  • Comfortable with structured, repetitive review work while maintaining accuracy.
  • Quick learning and consistent application of detailed annotation guidelines.
  • Strong written English communication skills.

Preferred

  • Experience with video annotation, data labeling, computer vision datasets, or egocentric video.

Start Date

  • Monday morning 17th August (PST)

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.