ZipRecruiter

Log In

1

Data Annotation Tech Jobs in Austin, TX (NOW HIRING)

Allen Control Systems

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

... drift, and annotation error; active-learning sampling to target gaps; feedback loops from ... Allen Control Systems develops autonomous defense technologies designed to detect, track, and ...

Allen Control Systems

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

... drift, and annotation error; active-learning sampling to target gaps; feedback loops from ... Allen Control Systems develops autonomous defense technologies designed to detect, track, and ...

Allen Control Systems

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

... drift, and annotation error; active-learning sampling to target gaps; feedback loops from ... Allen Control Systems develops autonomous defense technologies designed to detect, track, and ...

previous pagenext page

Showing results 21-40

All JobsData Annotation Tech JobsData Annotation Tech Jobs in Austin, TX

Data Annotation Tech information

See Austin, TX salary details

$12

$22

$34

How much do data annotation tech jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for 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 to become a data annotation tech?

To become a data annotation tech, you typically need a high school diploma or equivalent, strong attention to detail, and familiarity with data labeling tools or software. Some roles may require basic knowledge of machine learning concepts or specific platforms like Labelbox or CVAT. Gaining experience through online courses or tutorials can also improve job prospects.

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

To thrive as a Data Annotation Tech, you need keen attention to detail, basic computer literacy, and familiarity with data labeling standards, often supported by a high school diploma or equivalent. Experience with annotation platforms, image or text labeling tools, and basic knowledge of data management systems is highly valuable. Strong organizational skills, patience, and effective communication set top candidates apart in this field. These skills and qualities ensure annotated data is accurate, consistent, and valuable for machine learning or AI projects.

What does a data annotation tech do?

A typical day as a Data Annotation Tech involves reviewing large sets of data—such as images, text, or audio—and accurately labeling or categorizing them using specialized software. You may work independently or as part of a team, following specific project guidelines to ensure data integrity and consistency. Collaboration with project managers or data scientists is common when clarifying ambiguous data points or addressing annotation challenges. Additionally, productivity targets and quality checks are a regular part of the workflow, helping to keep projects on schedule and maintain high standards.

Does data annotation actually pay you?

Data annotation jobs typically pay hourly or per task, with rates varying depending on the platform and complexity of the work. Many companies and platforms offer remote opportunities that provide consistent payment once tasks are completed, often requiring basic skills in data labeling tools. Payment is generally reliable for those who meet quality standards and adhere to deadlines.

What is a data annotation tech?

A Data Annotation Tech is responsible for labeling and categorizing data, such as text, images, audio, or video, to train machine learning models. They follow specific guidelines to ensure accuracy and consistency in annotations, which helps improve the performance of AI systems. This role often involves repetitive tasks, attention to detail, and familiarity with various annotation tools. Data annotation is crucial for AI development in industries like healthcare, finance, and autonomous driving.

How much do data annotation technicians make?

Data annotation technicians typically earn between $12 and $20 per hour, depending on experience, location, and the complexity of the tasks. Many roles are entry-level and may offer flexible schedules or remote work opportunities.
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 Data Annotation Tech jobs in Austin, TX? For Data Annotation Tech jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Data Annotation Tech jobs in Austin, TX look for? The top searched job categories for Data Annotation Tech jobs in Austin, TX are:
What cities near Austin, TX are hiring for Data Annotation Tech jobs? Cities near Austin, TX with the most Data Annotation Tech job openings:
Data Annotation Tech jobs near you
Infographic showing various Data Annotation Tech job openings in Austin, TX as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $47,095 per year, or $22.6 per hour.

Shape the Future of AI -- Khmer Talent Hub

Welo Data

Austin, TX • On-site, Remote

Part-time

Re-posted 24 days ago

Job description

Are you detail-oriented and curious about tech?

Welo Data is building a global network of linguists, language enthusiasts, and culturally aware contributors to shape safer, smarter AI.

By joining our talent community, you’ll be first in line for flexible, remote projects in annotation, evaluation, and prompt creation—always on your terms.

Note: This is not an active job opening. By applying, you’ll join our global contributor network. When a project aligns with your skills and availability, we’ll reach out with all the details, including scope, timeline, and compensation.

What You’ll Need

- Native or near-native fluency in Central Khmer

- English proficiency

- Comfortable with digital tools

- Detail-oriented and curious

 

Why Join Us?

🚀 Limitless You – Work when and where you want, with room to grow

🤖 Limitless AI – Contribute to smarter, more inclusive AI

🌎 Be Part of Us – Join a global, supportive community

 

About our projects:

Welo Data projects vary by scope and complexity, but all play a role in building more accurate, inclusive, and human-centered AI.

Depending on your skills, you might:

📝 Annotate or label text, images, or audio to train AI systems

🔍 Evaluate search results, ads, or chatbot responses for quality and relevance

💬 Create and test prompts to improve large language models (LLMs)

🌍 Ensure content reflects cultural, linguistic, or industry-specific accuracy

Some projects last a few days; others may extend over several weeks. Before each one, you’ll receive clear details on tasks, timelines, and compensation, so you can decide what works best for you.

How to Apply?

Click the “Apply” button on our website to fill out a short form and join our talent database. It only takes a few minutes to get started and become part of our growing community.

Working at Welo Data

What to expect from working at Welo Data

From Welo Data

About Welo Data, in their own words

From Welo Data

Welo Data is a global AI data services company powering the next generation of AI. We build, annotate, and validate the training datasets that make AI models accurate, safe, and ready for the real world — across languages, cultures, and domains.

Our team of experts spans the globe, combining deep technical knowledge with a human-centered approach. If you want your work to shape how AI understands the world, you'll find your place here.

Diversity and inclusion statement

From Welo Data

Our Strength is derived from Winning Together. Welo Data is unequivocally committed to developing and fostering a workplace and organizational culture that values the diversity of thought and perspective delivered by a diverse global workforce operating within an inclusive organization.