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Flexible Data Annotation Tech Jobs in Austin, TX

Data preparation, annotation strategy, and labeling quality * Model evaluation, monitoring, and ... technologies across internal platforms and operational workflows. You will define technical ...

Support data annotation and quality validation activities * Maintain accurate operational records ... Work directly with cutting-edge robotics technology * Gain experience in one of the fastest-growing ...

Support data annotation and quality validation activities * Maintain accurate operational records ... Work directly with cutting-edge robotics technology * Gain experience in one of the fastest-growing ...

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Flexible Data Annotation Tech information

See Austin, TX salary details

$12

$22

$34

How much do flexible data annotation tech jobs pay per hour?

As of Aug 31, 2026, the average hourly pay for flexible data annotation tech in Austin, TX is $22.64, according to ZipRecruiter salary data. Most workers in this role earn between $16.68 and $26.92 per hour, depending on experience, location, and employer.

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 Austin, TX?

The most popular types of Data Annotation Tech jobs in Austin, TX are:

What are popular job titles related to Flexible Data Annotation Tech jobs in Austin, TX?

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

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

The top searched job categories for Flexible Data Annotation Tech jobs in Austin, TX are:

What cities near Austin, TX are hiring for Flexible Data Annotation Tech jobs?

Cities near Austin, TX with the most Flexible Data Annotation Tech job openings:

Infographic showing various Flexible Data Annotation Tech job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 26% Part Time, and 3% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $47,095 per year, or $22.6 per hour.

AI Trainer - Freelance Data Annotator

Mindrift - Data annotation

Austin, TX • Remote

$20/hr

Part-time

Re-posted 14 days ago


Job description

Please submit your resume in English and indicate your level of English proficiency.

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.

What this opportunity involves

Annotation is what helps AI make sense of the world. As an annotator, you may be invited to take part in online projects such as rating AI-generated content, evaluating factual accuracy, or comparing responses - when projects are available.

While each project involves unique tasks, contributors may:

  • Carefully review provided data (text, images, or videos);
  • Label or classify content based on project guidelines;
  • Identify and flag factually incorrect, sensitive, inappropriate, or unclear material.

What we look for

This opportunity is a good fit for candidates open to part-time, non-permanent projects. Ideally, contributors will have:

  • Bachelor's degree in any discipline;
  • Minimum 1 year of experience in any professional role;
  • Logical thinking, fact-checking and reasoning abilities;
  • Strong attention to detail and ability to understand and follow complex instructions;
  • Strong communication skills, including the ability to ask clarifying questions when needed;
  • Genuine interest in technology and artificial intelligence;
  • Strong written and spoken English (C1+).

How it works 

Apply Pass qualification(s)  Join a project (when available) Complete tasks Get paid

Why this freelance opportunity might be a great fit for you

  • Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments;
  • Participate into advanced AI projects and gain valuable experience that enhances your portfolio;
  • Influence how future AI models understand and communicate in your field of expertise.

Project time expectations

For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.

Compensation

Paid per accepted task. Your rate depends on the qualification tier you reach and how efficiently you complete tasks - up to the equivalent of $20/hr. Because payment is per task, a faster pace raises your effective hourly rate. Keep in mind, quality standards must be maintained, regardless of speed.