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Flexible Data Annotation Tech Jobs in Texas (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 ...

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Flexible Data Annotation Tech information

What is a flexible data annotation tech?

Flexible Data Annotation Tech jobs involve labeling, categorizing, or tagging data—such as images, text, audio, or video—to help train machine learning models. These roles are often remote or offer flexible schedules, making them appealing for those seeking adaptable work hours. Tasks can include identifying objects in photos, transcribing audio, or sorting information based on specific guidelines. The work is essential for improving the accuracy of artificial intelligence systems by providing them with high-quality annotated data. No advanced technical skills are usually required, but attention to detail and reliability are important.

What are the key skills and qualifications needed to thrive as a flexible data annotation tech, and why are they important?

To thrive as a Flexible Data Annotation Tech, you need attention to detail, accuracy, and a basic understanding of data labeling or annotation processes, often requiring at least a high school diploma. Familiarity with annotation platforms, data labeling tools, and productivity software is typically necessary, and experience with machine learning datasets can be advantageous. Strong time management, communication, and adaptability help you excel in collaborative and ever-changing project environments. These skills ensure high-quality, consistent data output that directly impacts the performance of AI and machine learning systems.

What are some common challenges faced by flexible data annotation techs, and how can they be addressed?

Flexible Data Annotation Techs often encounter challenges such as maintaining consistency across large volumes of data, adapting to evolving project guidelines, and managing tight deadlines. To address these challenges, it's important to establish clear communication with project leads, regularly review annotation protocols, and utilize available training resources. Building strong attention to detail and staying organized can also help ensure high-quality outputs and job satisfaction.

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

AspectFlexible Data Annotation TechData Labeler
CredentialsBasic computer skills, training in annotation toolsBasic education, sometimes specific software training
Work EnvironmentRemote or on-site, tech-focusedPrimarily remote or on-site, data processing settings
Industry UsageAI, machine learning, data scienceAI, machine learning, data preparation
Job FocusApplying labels to datasets using annotation toolsLabeling data according to guidelines

Flexible Data Annotation Tech roles involve using specialized tools to annotate datasets for AI training, often requiring some technical training. Data Labelers focus on applying labels to data, typically with less technical complexity. Both roles are essential in AI development but differ mainly in technical requirements and scope.

Can I do data annotation with no experience?

Data annotation roles often do not require prior experience, as training is typically provided to teach specific labeling tools and guidelines. Basic computer skills and attention to detail are usually sufficient to start, making it accessible for beginners. Over time, developing familiarity with annotation software and understanding data types can improve efficiency and accuracy.

Do data annotation jobs offer flexible hours?

Data annotation jobs often offer flexible hours, allowing workers to choose when they complete tasks, especially in freelance or remote roles. However, some positions may have specific deadlines or part-time schedules depending on the employer or platform used. Flexibility can vary based on the company's policies and project requirements.

What are the most commonly searched types of Data Annotation Tech jobs in Texas?

The most popular types of Data Annotation Tech jobs in Texas are:

What are popular job titles related to Flexible Data Annotation Tech jobs in Texas?

For Flexible Data Annotation Tech jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Flexible Data Annotation Tech jobs in Texas look for?

The top searched job categories for Flexible Data Annotation Tech jobs in Texas are:

What cities in Texas are hiring for Flexible Data Annotation Tech jobs?

Cities in Texas with the most Flexible Data Annotation Tech job openings:

Flexible Data Annotation Tech jobs near you
Infographic showing various Flexible Data Annotation Tech job openings in Texas as of June 2026, with employment types broken down into 86% Full Time, 11% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% 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

Posted 28 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