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How much do internship ai annotation writing jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for internship ai annotation writing in the United States is $15.54, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $17.55 per hour, depending on experience, location, and employer.

What is the difference between Internship Ai Annotation Writing vs Data Labeling Specialist?

AspectInternship Ai Annotation WritingData Labeling Specialist
CredentialsTypically students or entry-level with basic technical skillsOften requires experience with labeling tools and data management
Work EnvironmentInternship setting, often in tech or AI companiesFull-time or freelance roles in data annotation firms or tech companies
Industry UsageCommon in AI development, machine learning projectsUsed across AI, autonomous vehicles, and data-driven industries

Internship Ai Annotation Writing focuses on entry-level tasks like creating annotations for AI training data, often as part of an internship program. Data Labeling Specialist involves more experienced data annotation work, often with specialized tools and higher accuracy requirements. Both roles are essential in AI development but differ mainly in experience level and scope.

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Internship Ai Annotation Writing jobs near you
Infographic showing various Internship Ai Annotation Writing job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $32,333 per year, or $15.5 per hour.

Data Annotation Program Lead

Louisville, KY • On-site

SumasEdge Corporation
See more jobs at SumasEdge Corporationexternal

Other

Posted 4 days ago

Job description

We are looking for an Annotation Program Lead to manage our AI Quality Annotation Program. This individual will oversee the operational execution of human review activities that establish the gold-standard datasets used to measure conversational AI performance, safety, and compliance.

The ideal candidate combines strong program management skills with experience in quality assurance, data annotation operations, and stakeholder engagement.

Lead the day-to-day operation of the AI annotation program.

Manage a team of annotators responsible for reviewing customer conversations and AI interactions.

Develop annotation guidelines, procedures, and quality standards.

Establish calibration programs and quality assurance processes to ensure consistency across reviewers.

Partner with Data Scientists to create and maintain gold-standard datasets.

Monitor annotation accuracy, throughput, and quality metrics.

Coordinate reporting and deliverables for Legal, Compliance, Responsible AI, and executive stakeholders.

Manage annotation workflows and tooling including setting up annotation jobs, running data processing scripts, and testing annotation UIs for quality before job launch.

Plan capacity requirements to support seasonal increases in review volume.

Support future expansion into multilingual evaluation programs.

Identify process improvements that increase efficiency and annotation quality.

Bachelor's degree or equivalent experience in Linguistics/Psychology.

5+ years of experience in program management, operations, quality assurance, data labeling, or related fields.

Experience leading teams and managing operational workflows.

Strong organizational and stakeholder management skills.

Ability to analyze quality metrics and drive continuous improvement initiatives.

Excellent written and verbal communication skills.

Familiarity with Python/R, SQL and Excel. Should be familiar with running scripts on language data.

Strong organizational and stakeholder management skills.

Ability to analyze quality metrics and drive continuous improvement initiatives.

Excellent written and verbal communication skills.

Familiarity with Python/R, SQL and Excel. Should be familiar with running scripts on language data.

Experience supporting AI, machine learning, or data annotation programs.

Familiarity with Responsible AI, compliance, legal review, or governance processes.

Experience developing operational standards and quality frameworks.

Experience managing vendor or contractor resources.

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