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Internship Ai Data Annotation Jobs in Raleigh, NC

micro1 AI

AI Trainer - Microbiology Expert

Cary, NC · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

micro1 AI

AI Trainer - Microbiology Expert

Durham, NC · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

micro1 AI

AI Trainer - Microbiology Expert

Raleigh, NC · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

NCSU

Lecturer of Data Science

Raleigh, NC

$4.0K/wk

Introduction to AI Ethics, * Data Science for Social Good, * Introduction to Data Science for Cybersecurity * Measuring Success * Data Wrangling and Web Scraping, * Data Internships Preparation for ...

NCSU

Lecturer of Data Science

Raleigh, NC

$4.0K/wk

Introduction to AI Ethics, * Data Science for Social Good, * Introduction to Data Science for Cybersecurity * Measuring Success * Data Wrangling and Web Scraping, * Data Internships Preparation for ...

RELX

Data Discovery and Enrichment Expert II

Raleigh, NC · On-site +1

$71K - $119K/yr

Data Discovery and Enrichment Experts provide annotation, evaluation, and feedback to their partners which are critical to the development of these solutions.Examples of the innovative AI initiatives ...

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Internship Ai Data Annotation information

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

As of Aug 7, 2026, the average hourly pay for internship ai data annotation in Raleigh, NC is $21.88, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $23.85 per hour, depending on experience, location, and employer.

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 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 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.

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 most commonly searched types of Ai Data Annotation jobs in Raleigh, NC? The most popular types of Ai Data Annotation jobs in Raleigh, NC are:
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Internship Ai Data Annotation jobs near you
Infographic showing various Internship Ai Data Annotation job openings in Raleigh, NC as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 13% Part Time, and 6% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $45,502 per year, or $21.9 per hour.

AI Trainer - Microbiology Expert

micro1 AI

Cary, NC • Remote

$70 - $90/hr

Part-time

Posted 10 days ago

Job description

Role Title: Microbiologist


Role Type: Contractor


Location: Remote


micro1 is engaging Microbiologists to contribute their scientific expertise to a unique customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Key Responsibilities:

  1. Investigate and analyze the development, morphology, and behavior of microscopic organisms including bacteria, fungi, and algae.
  2. Contribute to the study of the relationship between microorganisms and disease, supporting projects involving medical microbiology.
  3. Assess the impact of antibiotics and other agents on microbial populations, providing insights for AI model accuracy.
  4. Document experimental findings and processes with a focus on clarity for AI training data.
  5. Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.
  6. Provide written and verbal expertise on microbiological phenomena and their relevance to real-world and computational contexts.
  7. Utilize rubrics and established evaluation criteria to assess data quality and support AI training workflows.


Required Skills and Qualifications:

  1. Bachelor’s degree or higher in Biology, Microbiology, Chemistry, or a related field.
  2. Extensive knowledge of bacterial, fungal, and algal systems.
  3. Demonstrated expertise in investigating microbial structure and physiology.
  4. Strong written and verbal communication skills for technical and interdisciplinary collaboration.
  5. Ability to document processes and findings clearly for integration into AI systems.
  6. Comfort working independently in a fully remote, digital-first environment.
  7. Attention to detail and commitment to scientific accuracy.


Preferred Qualifications:

  1. Prior experience developing or applying rubrics in scientific or educational contexts.
  2. Experience with AI, machine learning, or annotation projects related to biology or microbiology.
  3. Advanced degree (Master’s or PhD) in a relevant field.

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