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Contractual Remote Data Annotation Jobs in Columbia, SC

TSMG

AI/ML Data Contributor

Columbia, SC · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

TSMG

AI/ML Data Contributor

Columbia, SC · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

Bcbsa

Director of Audit - Synergie (Remote)

Columbia, SC · Remote

$150K - $200K/yr

Ensure audit work adheres to contractual standards and organizational policies. * Evaluate the ... Strong data management and analytics skills with the ability to manage large data effectively.

Amteck, LLC

Low Voltage Technician 3 - Columbia

Columbia, SC · On-site +1

$19.25 - $26.25/hr

... contractual documents and all applicable codes. Technician 3's can perform their job duties ... data jacks and mod plugs • Understand specifications of IDF and data closet enclosures and ...

Bcbsa

Financial Audit Senior Consultant

Columbia, SC · Remote

$107K/yr

Monitor, analyze, and evaluate assigned financial/accounting transactions and other financial data ... Evaluate the level of compliance with applicable federal regulations, contractual requirements, and ...

New

All JobsContractual Data Annotation JobsContractual Remote Data Annotation JobsContractual Remote Data Annotation Jobs in Columbia, SC

Contractual Remote Data Annotation information

What is contractual remote data annotation?

Contractual remote data annotation involves labeling or tagging data—such as images, text, or audio—while working from a remote location, usually as a contractor rather than a full-time employee. Data annotation is a crucial step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms learn to recognize patterns and make predictions. Contractors are typically assigned specific tasks or projects and are paid based on the volume or quality of their completed annotations. This type of work requires attention to detail, reliability, and sometimes domain-specific knowledge, depending on the project.

What is the difference between Contractual Remote Data Annotation vs Data Labeler?

AspectContractual Remote Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote or on-site, flexible or fixed hours
Industry UsageAI, machine learning, tech companiesAI, machine learning, tech companies
Job ScopeAnnotating data for training AI modelsLabeling data to train AI systems

Contractual Remote Data Annotation involves completing data annotation tasks on a contractual basis, often with flexible hours and remote work. Data Labelers perform similar tasks but may work on a freelance or part-time basis, sometimes in different environments. Both roles support AI development, but Contractual Remote Data Annotation typically emphasizes contractual agreements and remote flexibility.

What are the key skills and qualifications needed to thrive as a contractual remote data annotation specialist, and why are they important?

To thrive as a Contractual Remote Data Annotation Specialist, you need strong attention to detail, familiarity with data labeling concepts, and often a basic understanding of machine learning or AI workflows. Proficiency with annotation platforms like Labelbox, Supervisely, or Amazon SageMaker Ground Truth, as well as experience with common data types such as images, text, or audio, is typically required. Reliability, time management, and clear communication are essential soft skills for meeting deadlines and maintaining quality in remote, independent work. These skills and qualifications ensure accuracy and efficiency, which are critical for producing high-quality datasets that power AI and machine learning models.

What are some common challenges faced by contractual remote data annotators, and how can they be addressed?

Contractual remote data annotators often face challenges such as repetitive tasks, maintaining accuracy over long periods, and managing communication with distributed teams. To address these, it's important to establish a structured workflow, take regular breaks to prevent fatigue, and use quality control tools provided by employers. Staying proactive in seeking clarification on annotation guidelines and participating in team discussions can also help ensure consistent results and foster a supportive remote work environment.
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Contractual Remote Data Annotation jobs near you

AI/ML Data Contributor

TSMG

Columbia, SC • Remote

Full-time

Re-posted 11 days ago

Job description

Project Overview
We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing.

Projects may vary in scope and format, offering both remote and in-person opportunities (such as device or VR testing). This is a flexible, task-based role with the opportunity to participate in multiple projects over time.

Responsibilities
  • Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation
  • Participate in remote assignments or attend on-site sessions when required
  • Follow project guidelines and ensure high-quality task completion
  • Provide feedback and input during testing activities
  • Complete tasks within given timelines
Requirements
  • Must be based in the United States
  • Strong attention to detail and ability to follow instructions
  • Basic computer skills and familiarity with digital tools
  • Reliable internet connection and access to a computer or smartphone
  • Availability to participate in task-based work (schedule may vary)
Nice to Have
  • Previous experience in data annotation, QA, or testing
  • Interest in AI, machine learning, or emerging technologies
What We Offer
  • Paid, flexible task-based work
  • Opportunity to work on innovative AI/ML projects
  • Exposure to cutting-edge technologies (including device and VR testing)
  • Potential for ongoing project participation

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.