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Full Time Data Annotation Tech Jobs in Austin, TX

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Full Time Data Annotation Tech information

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$12

$22

$34

How much do full time data annotation tech jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for full time 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.

How much does a data annotation tech make per hour?

A full-time data annotation technician typically earns between $12 and $20 per hour, depending on experience, location, and the complexity of annotation tasks. Many roles require attention to detail and familiarity with annotation tools or platforms.

Can you do data annotation full time?

Full-time data annotation roles are available and typically involve working set hours, often 40 hours per week. These positions may require familiarity with annotation tools and attention to detail, and they often offer consistent schedules and remote or on-site options.

How hard is it to get hired by data annotation?

Getting hired as a full-time data annotation technician typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. The hiring process is generally straightforward, with many companies offering entry-level positions that do not require extensive experience or certifications.

How does a Full Time Data Annotation Tech typically collaborate with data scientists and engineers on projects?

As a Full Time Data Annotation Tech, you will regularly work alongside data scientists and engineers to ensure the accuracy and quality of labeled datasets used for machine learning models. Collaboration often involves attending project meetings to clarify annotation guidelines, providing feedback on ambiguous data cases, and updating annotation processes based on team input. Clear communication is essential, as your work directly impacts model performance and downstream analytics. This team-oriented environment fosters learning and provides insight into broader AI development workflows.

What are Full Time Data Annotation Techs?

Full Time Data Annotation Techs are professionals responsible for labeling and categorizing data used to train machine learning models. They examine various types of data, such as images, text, or audio, and apply specific tags or annotations according to project guidelines. Their work is essential in ensuring the accuracy of artificial intelligence systems by providing high-quality, structured datasets. Full-time positions typically involve working standard business hours and may require familiarity with specialized annotation tools and attention to detail.

What are the key skills and qualifications needed to thrive as a Full Time Data Annotation Tech, and why are they important?

To thrive as a Full Time Data Annotation Tech, you need strong attention to detail, basic data management skills, and familiarity with data labeling practices, typically supported by a high school diploma or equivalent. Experience with annotation tools (such as Labelbox, Supervisely, or similar platforms) and basic proficiency in spreadsheet or database systems are commonly required. Reliability, consistency, and effective communication are crucial soft skills for quality assurance and collaboration with data teams. These skills and qualities are essential to ensure the accuracy and efficiency of annotated datasets, which directly impact the performance of machine learning models.

What is the difference between Full Time Data Annotation Tech vs Data Labeling Specialist?

AspectFull Time Data Annotation TechData Labeling Specialist
CredentialsBasic computer skills, attention to detailSimilar credentials, often with training in labeling tools
Work EnvironmentOffice or remote, collaborative teamsRemote or on-site, focused on labeling tasks
Industry UsageAI, machine learning, tech companiesAI, autonomous vehicles, healthcare
Job FocusAnnotating data for machine learning modelsLabeling data to improve AI accuracy

Both roles involve data annotation and labeling, often requiring similar skills and working environments. The main difference lies in job titles used by employers and the scope of responsibilities, with 'Full Time Data Annotation Tech' emphasizing a broader technical role, while 'Data Labeling Specialist' may focus more on specific labeling tasks.

Can you make a living off data annotation?

Full Time Data Annotation Tech roles can provide a stable income, especially with consistent work and experience. However, pay rates vary depending on the employer, location, and complexity of tasks, and many positions are part-time or freelance, which may affect earning potential.
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:
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What job categories do people searching Full Time Data Annotation Tech jobs in Austin, TX look for? The top searched job categories for Full Time Data Annotation Tech jobs in Austin, TX are:
Full Time Data Annotation Tech jobs near you
Czech Data Labeling Analyst(Speech & Voice )

Czech Data Labeling Analyst(Speech & Voice )

Welocalize

Austin, TX

$26 - $28/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago

Welocalize rating

5.9

Company rating: 5.9 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

361st of 451 rated business services

Job description

Overview

Welo Data is looking for detail-oriented and reliable individuals to join our team as Data Labeling Analysts, supporting speech and voice AI systems.

This is a high-impact production role focused on building the datasets that power real-world AI systems. You’ll be working with audio, speech, and language data — helping ensure models are trained on accurate, well-structured, and representative inputs.

While this role is more execution-focused than evaluation-heavy roles, it still requires strong judgment, attention to detail, and consistency. The work sits at the intersection of language, data, and AI systems — where precision and discipline matter at scale.

We’re looking for people who are dependable, focused, and take pride in producing high-quality work, even across repetitive workflows.

Project Details
  • Job Title: Data Labeling Analyst
  • Hiring in: Onsite (Bay Area, Seattle, NYC, or client-dependent)
  • Hours: Full-time, 40 hours per week
  • Employment Type: W2 Full-Time Employee
  • Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship)
  • Pay Rate: $26 - $28/hour

Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: New York City, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, or Burlingame. Please only apply if you meet this location requirement.

What You'll Do
  • Execute high-volume data labeling and annotation tasks across speech and voice datasets
  • Follow detailed guidelines to ensure consistency, accuracy, and data integrity at scale
  • Work with audio and language data, including transcription, categorization, and tagging
  • Maintain strong throughput while meeting quality expectations
  • Escalate unclear or ambiguous cases appropriately
  • Adapt to evolving guidelines and workflows as systems and requirements change
  • Support baseline data production needs for AI training pipelines
  • Contribute to team calibrations and quality alignment sessions
What We're Looking For
  • Native-level fluency in Croatian
  • Strong written communication skills and language fundamentals
  • 1 year of work experience in data labeling, annotation, or content-focused work; or a Bachelor's degree or equivalent academic qualification in a related field.
  • Ability to follow detailed instructions and apply guidelines consistently
  • High attention to detail and ability to maintain accuracy in repetitive tasks
  • Comfort working in structured, process-driven environments
  • Ability to manage time effectively and maintain steady output
  • Willingness to ask questions and escalate when needed
  • Basic familiarity with AI, speech technology, or language data is a plus
Benefits
  • Paid Vacation: 6 days
  • Paid Company Holidays: 2 days (Memorial Day and Labor Day)
  • Paid Sick Leave: accrued per applicable state law and company policy
  • Medical, Dental, and Vision Insurance (eligibility applies)
  • Health Savings Account (HSA)
  • 401(k) Retirement Plan
  • Employee Assistance Program
  • Additional voluntary benefits (life, accident, critical illness, etc.)

Onsite Perks (where applicable):
Free breakfast, lunch, and dinner
Stocked micro-kitchens with snacks and beverages
Commuter benefits, including shuttles and bike-to-work options
Unique campus features depending on location

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