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Virtual Data Labelling Jobs in Florida (NOW HIRING)

Training Solutions Intern

Orlando, FL

$14 - $18.75/hr

Annotate images and video frames using designated labeling tools to support computer vision model ... Support data collection activities including motion capture, imaging, and sensor exercises.

Plan, design, and deploy Multi-Protocol Label Switching (MPLS) networks and designing systems that ... Apply relevant encryption standards for securing data traffic across wide area networks * Work with ...

Plan, design, and deploy Multi-Protocol Label Switching (MPLS) networks and designing systems that ... Apply relevant encryption standards for securing data traffic across wide area networks * Work with ...

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Virtual Data Labelling information

What is the difference between Virtual Data Labelling vs Data Annotation Specialist?

AspectVirtual Data LabellingData Annotation Specialist
CredentialsBasic computer skills, training in labelling toolsSimilar, often requires training in annotation software
Work EnvironmentRemote, online platformsRemote or on-site, depending on employer
Industry UsageAI, machine learning, autonomous vehiclesAI, computer vision, NLP projects
Search IntentLabeling data for AI modelsAnnotating data for machine learning

Both roles involve preparing data for AI systems, but Virtual Data Labelling focuses on assigning labels to datasets using online tools, while Data Annotation Specialists may perform more detailed annotations, often requiring specific domain knowledge. Both are essential in AI development and share similar work environments and skill requirements.

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the employer. Many roles are freelance or part-time, with some positions offering bonuses for accuracy or speed.

Is data labelling a good career?

Data labelling is a common entry-level role in data annotation and machine learning, offering opportunities to develop skills in data management and understanding AI workflows. It often requires attention to detail and familiarity with tools like annotation software, with flexible schedules and remote work options available. Career growth can lead to roles in data analysis, quality assurance, or AI development.

What is virtual data labelling?

Virtual data labelling is the process of annotating or tagging data, such as images, videos, or text, through online platforms to make it understandable for machine learning algorithms. Data labelers work remotely to identify and categorize objects, features, or information within datasets, which helps train artificial intelligence systems. This job is essential in industries like autonomous vehicles, healthcare, and e-commerce, where large volumes of labelled data are needed to improve AI accuracy.

How can I make $2000 a week working from home?

Virtual data labeling jobs can offer flexible income, but earning $2000 weekly typically requires completing a high volume of tasks or working multiple projects simultaneously. Success depends on experience, efficiency, and access to platforms that pay well, such as those offering premium or specialized labeling tasks.

How to make $1000 a week remote?

Virtual Data Labelling jobs can help you earn income remotely by labeling datasets for AI and machine learning projects. To make $1000 a week, you typically need to work consistently, complete high-volume labeling tasks efficiently, and possibly specialize in areas like image or audio annotation. Building a strong profile, gaining experience, and using platforms that pay well can increase your earning potential.

How does a virtual data labeller typically collaborate with data scientists and machine learning engineers?

Virtual data labellers play a crucial role in supporting data scientists and machine learning engineers by accurately tagging data that will be used to train and validate models. Collaboration often occurs through project management tools or direct communication platforms, where labellers receive guidelines and feedback to ensure consistency and quality. Regular check-ins or quality audits are common, and labellers may join virtual meetings to clarify requirements or discuss ambiguous cases. This teamwork helps ensure that the labelled data meets project standards and contributes to the success of AI initiatives.

What are the key skills and qualifications needed to thrive as a Virtual Data Labeller, and why are they important?

To thrive as a Virtual Data Labeller, you need strong attention to detail, accuracy, and basic data processing skills, typically supported by a high school diploma or relevant experience. Familiarity with data annotation tools, content management systems, and sometimes basic programming or spreadsheet software is important. Strong time management, focus, and effective communication skills help you meet deadlines and collaborate with remote teams. These abilities are crucial to ensure high-quality, consistent data labelling that directly impacts the performance of machine learning models.
What are the most commonly searched types of Data Labelling jobs in Florida? The most popular types of Data Labelling jobs in Florida are:
What are popular job titles related to Virtual Data Labelling jobs in Florida? For Virtual Data Labelling jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Virtual Data Labelling jobs in Florida look for? The top searched job categories for Virtual Data Labelling jobs in Florida are:
What cities in Florida are hiring for Virtual Data Labelling jobs? Cities in Florida with the most Virtual Data Labelling job openings:

$14 - $18.75/hr

Internship

Medical, Dental, Vision, Retirement, PTO

Posted 6 days ago


Job description

By Light Professional IT Services LLC readies warfighters and federal agencies with technology and systems engineered to connect, protect, and prepare individuals and teams for whatever comes next. Headquartered in McLean, VA, By Light supports defense, civilian, and commercial IT customers worldwide. 

Cole Engineering Services (CESI), a By Light company, is recognized as a premier provider of modeling and simulation (M&S) training solutions to the Federal Government and industry. Since 2004, CESI has been at the forefront of developing, maintaining, and integrating simulation-based training, serious gaming, technical services, training and other support in live, virtual, constructive, and gaming (LVCG) domains.  CESI also designs, builds and runs infrastructure, platforms, applications and processes that enable cyber training for the integrated multi-domain force. Our vision is to become a worldwide full spectrum LVCG and cyber training/analysis developer, integrator and services provider.


We are seeking a motivated intern to support the development of military training solutions. This position provides hands-on exposure while contributing directly to computer vision training pipelines through systematic image annotation. The intern will serve as a test subject in controlled, safe training scenarios.


  • Image Annotation for Computer Vision Training (Primary Duty):
    • Annotate images and video frames using designated labeling tools to support computer vision model development.
    • Apply bounding boxes, segmentation masks, keypoints, and classification tags per project specifications.
    • Maintain annotation accuracy and consistency in accordance with quality control standards.
    • Participate in adjudication reviews to reconcile annotation discrepancies.
    • Track annotation throughput and report progress to the project lead.
  • Test Target Participation:
    • Serve as a human test target in controlled training scenarios (safe, zero emissions, non-hazardous environments).
    • Support data collection activities including motion capture, imaging, and sensor exercises.
    • Follow all safety protocols and standard operating procedures during test events.
    • Provide structured feedback on participant experience to improve training realism.
  • Professional Environment Exposure:
    • Observe and participate in professional Military Environment workflows and briefings as a learning opportunity.
    • Shadow subject matter experts to build contextual understanding of training solution requirements.
    • Attend relevant team meetings, reviews, and demonstrations (non-operational, non-ME tasked).

  • Currently enrolled in an accredited undergraduate or graduate program (any relevant field).
  • Strong attention to detail and ability to perform repetitive precision tasks accurately.
  • Comfortable working in a structured, team-oriented professional environment.

  • Prior experience with image annotation platforms (e.g., CVAT, Labelbox, Scale AI, Roboflow).
  • Background in computer science, data science, cognitive science, or related discipline.
  • Familiarity with machine learning concepts or computer vision applications.

CESI recognizes that our strength is our people. We support every employee as an individual to build strong teams across the enterprise.  Our benefit package includes:

  • Medical, Dental & Vision Coverage
  • Wellness Program
  • 401(k) Matching
  • Disability (Short Term & Long Term)
  • Employee Assistance Program
  • Education & Training
  • Generous Leave Policy (11 Federal Holidays, PTO, Military Leave, Bereavement and Jury Duty)

CESI is committed to principles of inclusion and equal employment opportunity.  We foster a non-discriminatory, professional work environment for all our teams.  We do not discriminate based on race, color, religion, sex, pregnancy, sexual orientation, gender identity, genetic information, national origin, age, marital status, disability, or veteran status.


  • Office and controlled field environments; no hazardous emissions or exposure.
  • Test events are safe, scripted, and supervised by trained personnel.
  • Standard business hours with occasional schedule flexibility for test events.
  • Personal Protective Equipment (PPE) provided as required for test participation.