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Remote Entry Level Data Annotation Jobs in Ontario

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 ...

This role can be remote but needs to be able to visit local businesses in the GTA. What you'll do ... Data Continuity, Monitoring, and AAS offerings. * Demonstrate excellent customer service skills ...

Director, Support

Waterloo, ON · On-site +1

CA$85K - CA$104K/yr

Troubleshoot database and data-related issues in collaboration with development and support teams ... Work Experience (Entry-Level Friendly) * 0-2 years of professional experience supporting databases ...

Remote Entry Level Data Annotation information

What are the key skills and qualifications needed to thrive as a remote entry level data annotation?

To thrive as a Remote Entry Level Data Annotation specialist, you need strong attention to detail, basic computer literacy, and a high school diploma or equivalent. Familiarity with annotation platforms, data labeling tools, and sometimes basic spreadsheet software is typically required. Effective time management, communication, and the ability to follow precise instructions help candidates excel in this role. These skills ensure accurate, high-quality data labeling, which is crucial for training reliable machine learning models.

What is the difference between Remote Entry Level Data Annotation vs Remote Data Labeling Specialist?

AspectRemote Entry Level Data AnnotationRemote Data Labeling Specialist
CredentialsBasic computer skills, attention to detailSimilar, often no formal certifications required
Work EnvironmentRemote, flexible hoursRemote, often part-time or freelance
Industry UsageAI, machine learning, tech companiesAI, autonomous vehicles, tech firms
Search IntentEntry-level data annotation jobsData labeling roles for AI projects

Remote Entry Level Data Annotation and Remote Data Labeling Specialist roles are similar in credentials and work environment, both serving AI and machine learning industries. The main difference lies in terminology used by employers and job seekers, with 'Data Labeling Specialist' often emphasizing more specialized tasks. Both roles are suitable for individuals seeking remote, entry-level positions in data preparation for AI applications.

What are some common challenges faced by remote entry level data annotators, and how can they be managed?

Remote entry-level data annotators often encounter challenges related to maintaining focus and productivity while working independently, as well as ensuring consistency and accuracy in their annotations. To manage these challenges, it's helpful to establish a clear daily routine, set up a dedicated workspace, and actively communicate with team leads or supervisors for guidance. Utilizing collaboration tools and regularly reviewing project guidelines can also help maintain annotation quality and keep workflow on track.

What is a remote entry level data annotation?

A Remote Entry Level Data Annotation job involves labeling, tagging, or categorizing data such as images, text, audio, or video from a remote location. These roles are crucial for training machine learning algorithms, as annotated data helps improve the accuracy of artificial intelligence models. Entry-level positions typically require attention to detail and basic computer skills but do not usually require prior experience or specialized knowledge. Working remotely allows you to perform these tasks from home or any location with internet access.
What are popular job titles related to Remote Entry Level Data Annotation jobs in Ontario? For Remote Entry Level Data Annotation jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Remote Entry Level Data Annotation jobs in Ontario look for? The top searched job categories for Remote Entry Level Data Annotation jobs in Ontario are:
What cities in Ontario are hiring for Remote Entry Level Data Annotation jobs? Cities in Ontario with the most Remote Entry Level Data Annotation job openings:
Infographic showing various Remote Entry Level Data Annotation job openings in Ontario as of July 2026, with employment types broken down into 70% Full Time, 21% Part Time, 3% Temporary, and 6% Contract. Highlights an 100% Remote job distribution.

Copy of CFD & Aerodynamic Engineer (AI Training & Evaluation)

Lifted, an Upwork Company™

Ottawa, ON • Remote

Contractor

Posted 5 days ago


Job description

Company Description

An enterprise client is seeking CFD & Aerodynamic Engineers to help train and evaluate next-generation AI systems by contributing real-world engineering expertise.

This opportunity is offered by a leading AI data platform that enables organizations to build intelligent applications powered by high-quality human expertise.

    Job Description

    This opportunity is ideal for experienced CFD and Aerodynamics Engineers who enjoy solving complex engineering problems and want to contribute their expertise to the development of advanced AI systems.

    What You'll Do:

    • Design compact, self-contained CFD and aerodynamics tasks that evaluate AI models' engineering reasoning.
    • Create clear and technically accurate problem statements covering topics such as boundary conditions, mesh quality, flow regimes, and simulation setup.
    • Develop deterministic scoring checkers that objectively evaluate AI-generated responses.
    • Produce verified reference solutions to ensure each task is technically accurate and fully solvable.
    • Review and refine engineering tasks to improve clarity, physical accuracy, and appropriate difficulty.
    • Apply real-world experience with OpenFOAM to develop practical and realistic engineering scenarios.
    • Work independently in a fully remote, asynchronous environment with complete scheduling flexibility.
    Qualifications

    Requirements:

    • Bachelor's degree (or higher) in Aerospace Engineering, Mechanical Engineering, or a closely related discipline.
    • Hands-on experience using OpenFOAM for computational fluid dynamics simulations.
    • Strong foundation in fluid mechanics, aerodynamics, and heat transfer principles.
    • Experience with:
      • Mesh generation
      • Turbulence modeling
      • Boundary condition specification
      • Post-processing and simulation analysis
    • Ability to write clear, precise, and objectively verifiable engineering problems.
    • Excellent written English communication skills with the ability to explain complex technical concepts clearly.
    • Self-motivated, detail-oriented, and able to work independently with minimal supervision.

    Nice to Haves:

    • Experience working on aerospace, automotive, motorsports, renewable energy, or industrial CFD applications.
    • Familiarity with advanced CFD validation and verification techniques.
    • Experience reviewing technical documentation or engineering research.
    • Previous experience contributing to AI, simulation, or data annotation projects.

    Additional Information
    • Fully remote, independent contractor opportunity.
    • Flexible schedule with an expected workload of 10–39 hours per week, depending on project demand.
    • Compensation ranges from $80–$110 USD per hour, based on qualifications and experience.
    • Payments are issued weekly for completed work from the previous week.
    • If selected, you will receive an Upwork contract offer along with onboarding instructions for the client's task platform.
    • To be considered, candidates must:
      • Submit an Upwork proposal.
      • Complete the required Google Form.
      • Accept the Upwork contract to receive onboarding instructions, assessment access, and project payments.
    • Due to the high volume of applicants, only shortlisted candidates will be contacted.