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Intern Data Annotation Tech Jobs in Frisco, TX (NOW HIRING)

Expert Technology Services

Data Annotator

Irving, TX · On-site

$109K - $132K/yr

Data Annotator & QA Reviewer - Autonomy & Robotics (Mining) - Perform manual data annotation and quality assurance (QA) review for perception and VLA (Vision-Language-Action) data, including video ...

Workiva

Spring 2027 Intern - Data Analytics

Mckinney, TX · On-site

$22/hr

The Data Research and Collection Intern collects and interprets data for our customers affected by ... At Workiva, you'll bring technology to market that executives, boards, and regulators depend on.

Workiva

Spring 2027 Intern - Data Analytics

Mckinney, TX · On-site +1

$22/hr

The Data Research and Collection Intern collects and interprets data for our customers affected by ... At Workiva, you'll bring technology to market that executives, boards, and regulators depend on.

Copart, Inc.

Data Engineering Intern

Dallas, TX · On-site

Copart, Inc. a technology leader and the premier online vehicle auction platform globally, with ... The Data Engineer Intern will be part of the Data Engineering Team. The Data Engineering team works ...

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All JobsIntern Data Annotation Tech JobsIntern Data Annotation Tech Jobs in Frisco, TX

Intern Data Annotation Tech information

What is an intern data annotation tech?

Intern Data Annotation Techs are entry-level professionals, often students or recent graduates, who support machine learning projects by labeling and categorizing data, such as images, text, or audio. Their work is essential for training AI systems, as accurately annotated data helps algorithms learn to make correct predictions. These interns typically use specialized software tools to tag or classify data according to specific guidelines. The role requires attention to detail, consistency, and sometimes basic technical skills, depending on the complexity of the data and tasks. Internships in data annotation can provide valuable exposure to the fields of artificial intelligence and data science.

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

To thrive as an Intern Data Annotation Tech, you need attention to detail, basic data management skills, and familiarity with data labeling concepts, often supported by a high school diploma or ongoing college coursework. Experience with annotation platforms, spreadsheet tools, and sometimes basic scripting languages is helpful. Strong communication, reliability, and the ability to follow detailed instructions are valuable soft skills in this role. These abilities ensure accurate and efficient data labeling, which is critical for training reliable machine learning models.

What are some common challenges faced by intern data annotation techs, and how can they overcome them?

Intern Data Annotation Techs often encounter challenges such as maintaining consistency in labeling large datasets and understanding nuanced instructions for annotation tasks. To overcome these hurdles, it's important to ask clarifying questions early on, regularly review annotation guidelines, and participate in team discussions about edge cases. Collaboration with more experienced annotators and feedback from supervisors also help in refining skills and ensuring high-quality data preparation. Developing attention to detail and adaptability will contribute to a successful internship experience.

What is the difference between Intern Data Annotation Tech vs Intern Data Labeler?

AspectIntern Data Annotation TechIntern Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentData annotation platforms, remote or officeData labeling platforms, remote or office
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Job FocusAnnotating data for training AI modelsLabeling data for machine learning algorithms

Both roles involve preparing data for AI systems, with similar skills and work environments. The main difference lies in terminology; 'Data Annotation Tech' emphasizes technical annotation tasks, while 'Data Labeler' is a more general term. Both are entry-level positions vital for training AI models in the tech industry.

Can I do data annotation with no experience?

Intern Data Annotation Tech roles often do not require prior experience, as training is typically provided to teach skills like image or text labeling using annotation tools. Basic computer skills and attention to detail are usually sufficient to start, making it accessible for beginners. Developing familiarity with annotation software and understanding data quality standards can improve job performance over time.

Does data annotation tech actually pay?

Data annotation technicians are paid for their work, with wages typically ranging from minimum wage to higher rates depending on experience, complexity of tasks, and the employer. Payment is usually hourly or per task, and some roles may require basic skills in data labeling tools or software. Compensation varies by company and location but generally provides a reliable income for entry-level positions.

Is it hard to get hired for data annotation?

Getting hired as a data annotation intern typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools. Many positions are entry-level and may not require extensive experience, making the application process relatively accessible for beginners. However, competition can vary depending on the company and location.

What are popular job titles related to Intern Data Annotation Tech jobs in Frisco, TX?

For Intern Data Annotation Tech jobs in Frisco, TX, the most frequently searched job titles are:

What job categories do people searching Intern Data Annotation Tech jobs in Frisco, TX look for?

The top searched job categories for Intern Data Annotation Tech jobs in Frisco, TX are:

Intern Data Annotation Tech jobs near you
Infographic showing various Intern Data Annotation Tech job openings in Frisco, TX as of September 2026, with employment types broken down into 33% Full Time, and 67% Part Time. Highlights an 33% In-person, and 67% Remote job distribution.

AI Training Specialist (Data Annotation)

Dallas, TX • On-site, Remote

Remote Talent Cloud
See more jobs at Remote Talent Cloudexternal

$20/hr

Contractor

Re-posted 8 days ago

Job description

As an AI Training Specialist (Data Annotation), you'll play a key role in helping train and improve artificial intelligence (AI) systems. Your work will directly support how AI models learn to recognize text, images, and other data accurately.
Your main responsibilities will include:
  • Labeling and categorizing data (such as text, images, or short videos) according to detailed project guidelines
  • Reviewing and verifying data for accuracy, consistency, and completeness
  • Identifying and flagging any errors, inconsistencies, or unclear data
  • Following clear annotation instructions to ensure high-quality results
  • Meeting productivity and accuracy goals within project timelines
  • Maintaining confidentiality and adhering to all data security standards

Requirements
We're looking for detail-oriented individuals who are comfortable working independently and enjoy structured, accuracy-focused tasks. The ideal candidate will have:
  • This is a fully remote position, but you must be located within the United States
  • Excellent attention to detail and strong organizational skills
  • A reliable Internet connection and computer
  • The ability to focus for extended periods and follow detailed written instructions
  • Strong written communication skills in English
  • Previous data annotation, labeling, or transcription experience is a plus, but not required

Benefits
  • Fully remote: work from anywhere within the United States
  • Full-time and part-time available
  • Competitive hourly pay from $20/hr
  • Training provided for all annotation tools and workflows
  • Gain hands-on experience supporting real-world AI training projects
  • Be part of a growing remote team working on cutting-edge technology

Apply