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Internship Ai Data Labeling Jobs (NOW HIRING)

Aerotek

Data Labeling Specialist

San Jose, CA · On-site

$30/hr

🚀 Data Labeling Specialist - AI & Robotics 💡 No prior experience required -- All training will be provided Join our mission to build the world's first general-purpose humanoid robot. As a Data ...

Reducto

Data Labeling Lead (Contract)

Reducto is the agentic document platform for leading AI teams who demand enterprise performance at ... The Opportunity As Data Labeling Lead , you'll play a key role in leading and managing our in-house ...

Pareto AI

AI Engagement Manager

$150K - $180K/yr

Partner with Product, Delivery, and Engineering to design solutions for Agentic AI, data labeling, evaluation, RLHF, red-teaming, and emerging workflows * Ensure strong requirements gathering ...

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Internship Ai Data Labeling information

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How much do internship ai data labeling jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for internship ai data labeling in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

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

AspectInternship Ai Data LabelingData Annotation Specialist
Required CredentialsHigh school diploma or equivalent; some technical skillsHigh school diploma or higher; technical skills often preferred
Work EnvironmentEntry-level, training-focused, often remote or in-officeProfessional setting, may be remote or on-site, more independent
Employer & Industry UsageTech companies, AI startups, research projectsAI companies, data service providers, tech firms
Search & Comparison IntentUnderstanding entry-level roles in AI data labelingClarifying professional data annotation roles

Internship Ai Data Labeling typically refers to entry-level, training-focused positions aimed at gaining experience in labeling data for AI models. Data Annotation Specialist is a more experienced, professional role involving detailed data labeling tasks. Both roles are essential in AI development, but internships are designed for beginners, while specialists have more responsibility and expertise.

What is an AI Data Labeling Internship?

An AI Data Labeling Internship is a temporary position where interns assist in preparing datasets for machine learning models by accurately annotating, categorizing, or tagging data such as images, text, or audio. Interns learn about the fundamentals of artificial intelligence and the importance of high-quality labeled data in training algorithms. This role is ideal for students or recent graduates interested in AI, data science, or related fields, and provides hands-on experience with data preparation and quality assurance processes.

What are some common challenges faced during an AI Data Labeling internship, and how can I overcome them?

As an AI Data Labeling intern, you may encounter challenges such as maintaining high accuracy while labeling large volumes of data, understanding complex labeling guidelines, and managing repetitive tasks without losing focus. To overcome these, it's helpful to regularly review the instructions, seek feedback from your team lead, and use productivity techniques to stay engaged. Collaborating with other interns and attending team meetings can also provide valuable insights and help you address uncertainties quickly.

What are the key skills and qualifications needed to thrive as an AI Data Labeling Intern, and why are they important?

To thrive as an AI Data Labeling Intern, you need attention to detail, basic data analysis skills, and familiarity with data annotation concepts, often supported by a background in computer science or related fields. Experience using annotation platforms, spreadsheets, and sometimes specific labeling software is common, though formal certifications are not usually required. Strong communication, time management, and the ability to follow detailed guidelines set high performers apart in this role. These skills ensure accurate, high-quality data sets that are essential for training reliable AI models.
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Internship Ai Data Labeling jobs near you
Infographic showing various Internship Ai Data Labeling job openings in the United States as of May 2026, with employment types broken down into 60% Full Time, and 40% Part Time. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

AI Data Labeling & Quality Specialist

TPI Global (formerly Tech Providers, Inc.)

Fort Mill, SC • On-site

$15.50 - $20.25/hr

Full-time

Posted 4 days ago

Job description

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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