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Annotation Labelling Jobs in South Carolina (NOW HIRING)

TSMG

AI/ML Data Contributor

Columbia, SC · On-site

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

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

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 · On-site

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 · On-site

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

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 ...

All JobsAnnotation Labelling JobsAnnotation Labelling Jobs in South Carolina

Annotation Labelling information

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What are the key skills and qualifications needed to thrive as an annotation labelling specialist?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by annotation labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

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

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

What are popular job titles related to Annotation Labelling jobs in South Carolina? For Annotation Labelling jobs in South Carolina, the most frequently searched job titles are:
What job categories do people searching Annotation Labelling jobs in South Carolina look for? The top searched job categories for Annotation Labelling jobs in South Carolina are:
Annotation Labelling jobs near you

AI Data Labeling & Quality Specialist

TPI Global (formerly Tech Providers, Inc.)

Fort Mill, SC • On-site

$15.50 - $20.25/hr

Temporary

Re-posted just now

Job description


bilingual AI Data Labelling & Quality Specialist
3-6 Months possibility of conversion
Fort mill, SC (Remote role)
About the role:
  • We are seeking a bilingual AI Data Labelling & Quality Specialist to support the development of an AI-assisted sales system for our Home Services business.
  • This includes both a voice agent and tools for human sales agents, designed to deliver highly personalized customer journeys.
  • The ideal candidate will help improve our AI models by labelling ground-truth data, evaluating AI outputs, and providing structured feedback to enhance multilingual performance-in English and Spanish.

Responsibilities
  • Review, label, and categorize customer interaction data (audio and text) to create high-quality training datasets.
  • Evaluate AI/LLM outputs for accuracy, clarity, tone, and compliance with internal guidelines.
  • Provide detailed feedback to improve AI behaviors, dialog flows, and multilingual consistency.
  • Identify patterns, edge cases, and opportunities to increase the effectiveness of English and Spanish customer experiences.
  • Ensure data quality, confidentiality, and adherence to annotation standards.

Qualifications
  • Fluent in English and Spanish (spoken and written) with strong comprehension and communication skills.
  • Prior experience in data labelling, annotation, linguistics, QA, customer support, or AI training.
  • Familiarity with conversational AI, LLMs, or voice agents is a plus.
  • Strong attention to detail and ability to follow structured guidelines.
  • Comfortable working with productivity tools and web-based annotation platforms.
  • Ability to work independently, meet deadlines, and adapt to evolving requirements.

Meet Your Recruiter
Mohit Sharma

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