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Annotation Labelling Jobs in North Carolina (NOW HIRING)

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, and why are they important?

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 North Carolina? For Annotation Labelling jobs in North Carolina, the most frequently searched job titles are:
What job categories do people searching Annotation Labelling jobs in North Carolina look for? The top searched job categories for Annotation Labelling jobs in North Carolina are:
What cities in North Carolina are hiring for Annotation Labelling jobs? Cities in North Carolina with the most Annotation Labelling job openings:

Python Developer _ MRM & Data Annotation (AI/ML)

Tata Consultancy Service Limited

Charlotte, NC • On-site

$110K - $125K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 15 days ago


Job description

Must Have Technical/Functional Skills
Python , MRM , Data Annotator ,Agile concepts, CI/CD
10+ years experience
Roles & Responsibilities
• 10+ years of hands experience in Python , MRM , Data Annotator
• Build and maintain Python pipelines for data ingestion, preprocessing, and model feature preparation.
• Implement MRM controls such as model documentation, versioning, validation evidence, and audit trails.
• Develop tools for annotation workflow automation (task assignment, QA sampling, and label consistency checks).
• Collaborate with risk, compliance, and data science teams to align model development with governance standards.
• Create reproducible training/evaluation scripts with clear experiment tracking and model lineage.
• Define and monitor model performance, drift, and data quality metrics across lifecycle stages.
• Design labeling guidelines and enforce annotation standards to improve downstream model reliability.
• Perform root-cause analysis for model errors and annotation defects, then drive corrective actions.
• Build APIs/utilities for secure data access, transformation, and integration with internal platforms.
• Support model validation activities with technical artifacts, assumptions, and testing evidence.
• Ensure adherence to data privacy, security, and responsible AI policies in all workflows.
• Document SOPs, handover notes, and technical runbooks for operational continuity.
Generic Managerial Skills, If any
• Proactive and result-oriented leader, adept in mentoring and motivating the dynamic team to exemplary performance.
• Strong communication, collaboration, and team building skills with proficiency in grasping new technical concepts quickly
TCS Employee Benefits Summary:
Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options: Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
Time Off: Vacation, Time Off, Sick Leave & Holidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
Salary Range: $110,000-$125,000 a year