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Remote Data Annotation Jobs in Toronto, ON (NOW HIRING)

Network Engineer - Data for Autonomous Systems annotation Type: Contract Compensation: $50-$70/hour Location: Remote Commitment: 30-40 hours/week Role Responsibilities * Review real-world data from ...

Network Engineer - Data for Autonomous Systems annotation Type: Contract Compensation: $50-$70/hour Location: Remote Commitment: 30-40 hours/week Role Responsibilities * Review real-world data from ...

Network Engineer

Toronto, ON · Remote

CA$50 - CA$70/hr

Network Engineer - Data for Autonomous Systems annotation Type: Contract Compensation: $50-$70/hour Location: Remote Commitment: 30-40 hours/week Role Responsibilities * Review real-world data from ...

Network Support Engineer

Toronto, ON · Remote

CA$50 - CA$70/hr

Network Engineer - Data for Autonomous Systems annotation Type: Contract Compensation: $50-$70/hour Location: Remote Commitment: 30-40 hours/week Role Responsibilities * Review real-world data from ...

Network System Engineer

Toronto, ON · Remote

CA$50 - CA$70/hr

Network Engineer - Data for Autonomous Systems annotation Type: Contract Compensation: $50-$70/hour Location: Remote Commitment: 30-40 hours/week Role Responsibilities * Review real-world data from ...

Toronto, Ontario (Initially Remote) About Us: NTENT provides a Platform-as-a-Service (PaaS ... Coordinate data collection and annotation efforts. * Work with real-time data and content coming ...

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Remote Data Annotation information

See Toronto, ON salary details

$9

$32

$72

How much do remote data annotation jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for remote data annotation in Toronto, ON is $32.69, according to ZipRecruiter salary data. Most workers in this role earn between $16.75 and $42.44 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Remote Data Annotation position, and why are they important?

To thrive as a Remote Data Annotation specialist, strong attention to detail, accuracy, and familiarity with basic data processing concepts are essential, often requiring a high school diploma or equivalent. Experience using data labeling platforms, annotation tools (such as Labelbox or Supervisely), and sometimes familiarity with spreadsheet software may be required. Excellent time management, communication skills, and the ability to work independently are valuable soft skills in this remote role. These skills are vital to ensure that data annotations are consistent, precise, and delivered on schedule, which directly impacts the quality of AI and machine learning outcomes.

What are the typical daily tasks for someone working in Remote Data Annotation?

Daily tasks for a Remote Data Annotation role usually involve reviewing and labeling large volumes of data—such as images, audio clips, text, or video—according to specific project guidelines. You will use specialized annotation tools to identify objects, transcribe content, categorize information, or tag relevant features to support machine learning projects. Communication with project managers or quality assurance teams may be necessary for feedback and clarity on guidelines. Most roles also require regular self-checks for accuracy and the ability to meet productivity quotas or deadlines. This structure allows for a combination of focused individual work and occasional team collaboration to ensure project goals are met.

What is a Remote Data Annotation job?

A Remote Data Annotation job involves labeling, tagging, or categorizing data (such as images, text, audio, or video) to help improve machine learning models. This work is typically done from home using specialized annotation tools provided by employers. Accuracy and attention to detail are essential, as the quality of annotations directly impacts AI model performance. Many companies hire remote annotators on a freelance, part-time, or contractual basis.

What are popular job titles related to Remote Data Annotation jobs in Toronto, ON? For Remote Data Annotation jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Remote Data Annotation jobs in Toronto, ON look for? The top searched job categories for Remote Data Annotation jobs in Toronto, ON are:
What cities near Toronto, ON are hiring for Remote Data Annotation jobs? Cities near Toronto, ON with the most Remote Data Annotation job openings:

Network Specialist - Fully Remote

Mercor

Toronto, ON • Remote

CA$50 - CA$70/hr

Full-time

Posted 8 days ago


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: Network Engineer - Data for Autonomous Systems annotation
Type: Contract
Compensation: $50–$70/hour
Location: Remote
Commitment: 30–40 hours/week

Role Responsibilities

  • Review real-world data from deployed networks, including logs, configs, telemetry, and event streams.
  • Label and classify key behaviors, issues, and anomalies in network data.
  • Help define schemas and structure for large-scale data pipelines.
  • Interface directly with the client team to ensure data quality and relevance.
  • Work independently and asynchronously to meet deadlines and improve AI model performance.

Qualifications

Must-Have

  • Experience working as a network engineer, ideally with enterprise networks (switches, APs, firewalls, etc.).
  • Comfort with interpreting logs, events, and time-series metrics.
  • Curiosity about how raw infrastructure data becomes machine learning input.

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.