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Internship Ai Data Annotation Jobs (NOW HIRING)

YO AI Labs

AI Data Science Expert - Remote

Palo Alto, CA · Remote

$100 - $200/hr

Job Title: AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job ... Data Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving

YO AI Labs

AI Data Science Expert - Remote

Miami, FL · Remote

$100 - $200/hr

Job Title: AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job ... Data Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving

Jobgether

$2 - $5/hr

Our partner is looking for a Video Annotation & Data Labeling Specialist based in Netherlands. This ... Review AI-generated captions and identify or correct inaccuracies, inconsistencies, and unclear ...

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

As of Sep 2, 2026, the average hourly pay for internship ai data annotation 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 an AI data annotation internship?

An AI Data Annotation Internship is a temporary position where interns help label, tag, or categorize data (such as images, text, or audio) to train and improve artificial intelligence models. Interns typically work with datasets, ensuring that the information provided is accurate and consistent, which is crucial for machine learning algorithms to learn effectively. The role is a valuable entry point for those interested in AI, machine learning, or data science, as it offers hands-on experience with the foundational work needed to build intelligent systems.

What are the key skills and qualifications needed to thrive as an AI data annotation intern?

To thrive as an Internship AI Data Annotation specialist, you need attention to detail, basic computer literacy, and a foundational understanding of data labeling concepts, often supported by ongoing training or coursework in data science or computer science. Familiarity with annotation tools like Labelbox, Supervisely, or VIA, and knowledge of data management platforms are commonly required. Strong organizational skills, patience, and effective communication help you manage repetitive tasks and collaborate with team members. These skills are essential to ensure high-quality data labeling, which directly impacts the performance and accuracy of AI models.

What are the typical challenges faced during an AI data annotation internship, and how can I overcome them?

As an AI Data Annotation intern, you may encounter challenges such as maintaining high accuracy while labeling large volumes of data, understanding complex annotation guidelines, and adapting to evolving project requirements. It's important to regularly communicate with your team lead or project manager to clarify any uncertainties and ensure consistency in your annotations. Leveraging available training materials and asking for feedback will help you improve your efficiency and accuracy, turning these challenges into valuable learning experiences.

What is the difference between Internship Ai Data Annotation vs Data Labeler?

AspectInternship Ai Data AnnotationData Labeler
CredentialsHigh school diploma or equivalent; some roles prefer basic technical skillsHigh school diploma or equivalent; minimal formal education required
Work EnvironmentOffice or remote; supervised tasks, often part-time or temporaryOffice or remote; repetitive tasks, often entry-level
Industry UsageTech companies, AI startups, research projectsTech firms, data companies, AI development teams
Search & Comparison IntentUnderstanding entry-level roles in AI data annotationComparing entry-level data labeling jobs in AI

Internship Ai Data Annotation roles typically involve supervised, short-term tasks aimed at gaining experience in AI data preparation. Data Labeler positions are similar entry-level roles focused on labeling data for machine learning. Both roles require basic skills and are used across tech and AI industries, but internships often offer more training and learning opportunities.

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Internship Ai Data Annotation jobs near you
Infographic showing various Internship Ai Data Annotation job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

AI Data Science Expert - Remote

YO AI Labs

New York, NY • Remote

Part-time

Posted 24 days ago

Job description

Job Title: AI Data Science Domain Expert

Job Type: Contractor (Part-Time)
Location: Remote

Job Overview

We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative project focused on advancing next-generation AI systems. In this role, you will review, evaluate, and refine AI-generated technical and analytical content to improve model accuracy, reasoning, and overall performance. No prior AI experience is required—your data science expertise, analytical thinking, and communication skills are what matter most.

Key Responsibilities
  • Review, edit, and refine AI-generated content for accuracy, clarity, and technical relevance.
  • Develop, optimize, and evaluate prompts to improve AI model performance.
  • Conduct rubric-based assessments of AI outputs and provide structured feedback.
  • Perform independent research and fact-checking to validate technical information.
  • Annotate data and support quality assurance initiatives for AI training.
  • Interpret complex datasets and prepare clear technical reports and summaries.
  • Collaborate remotely with project teams to improve AI models and workflows.
Required Skills
  • Critical Thinking
  • Analytical Reasoning
  • Prompt Engineering
  • AI Output Evaluation
  • Quality Assurance
  • Technical Documentation
  • Technical & Report Writing
  • Content Review & Editing
  • Data Annotation
  • Data Interpretation
  • Fact Checking
  • Independent Research
  • Problem-Solving
  • Attention to Detail
Preferred Qualifications
  • 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.
  • Experience producing or reviewing research papers, analytical reports, technical documentation, experiment summaries, or data-driven recommendations.
  • Strong analytical reasoning, critical thinking, and written communication skills.
  • Experience with data annotation, content review, or rubric-based evaluation is preferred.
  • Familiarity with prompt engineering, AI output evaluation, fact-checking, or RLHF is a plus.
  • Master's, MBA, PhD, or other advanced degree is preferred.