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Data Annotation Jobs in Texas (NOW HIRING)

Arrive Logistics

Data Scientist II

Austin, TX · On-site

... annotation guidelines and ensuring label quality. • Evaluate and apply the appropriate approach ... data. • Perform structured analysis of system performance to surface failure modes, data gaps ...

TSMC

Senior Data Engineer / Data Curator

Austin, TX · On-site

$105K - $142K/yr

... data annotation tools and platforms for manual or semi-automated labeling. • Experience with NLP data formats, such as JSONL, text, or embeddings, and an understanding of tokenization. • ...

Apple

Senior Manager - AI Data Operations

Austin, TX

Description You will lead an organization of internal domain experts, building scalable annotation ... You will partner closely with Engineering, Data Science, and Programs to translate evolving system ...

Arrive Logistics

Data Scientist II

Austin, TX · On-site

Experience designing data annotation workflows, labeling guidelines, or label quality processes is ... a plus. * Experience with model deployment, monitoring, or production ML workflows is a plus.

Arrive Logistics

Data Scientist II

Austin, TX · On-site +1

Experience designing data annotation workflows, labeling guidelines, or label quality processes is ... a plus. * Experience with model deployment, monitoring, or production ML workflows is a plus.

RWS TrainAI

Language Data Annotator (US)

Dallas, TX · On-site +1

Experience in one or more of the following areas: machine learning tasks, data collection and preprocessing, data evaluation and quality assurance, and data annotation and labeling. What We Offer

RWS TrainAI

Language Data Annotator (US)

Dallas, TX · On-site +1

Experience in one or more of the following areas: machine learning tasks, data collection and preprocessing, data evaluation and quality assurance, and data annotation and labeling. What We Offer

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How much do data annotation jobs pay per hour?

As of Jul 1, 2026, the average hourly pay for data annotation in Texas is $22.19, according to ZipRecruiter salary data. Most workers in this role earn between $15.01 and $26.43 per hour, depending on experience, location, and employer.

What does a typical workday look like for someone in a Data Annotation role?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

Is data annotation a genuine job?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to help train machine learning models. It often requires attention to detail and familiarity with annotation tools, and can be found in various industries like technology and healthcare.

Does data annotation pay well?

Data annotation jobs typically offer entry-level pay that varies depending on the employer, location, and complexity of the tasks. While some positions pay hourly wages comparable to other administrative or clerical roles, experienced annotators working on specialized projects or with advanced tools can earn higher rates. Overall, data annotation is often considered an entry-level position with moderate pay potential.

What is a Data Annotation job?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

How hard is it to get hired by data annotation?

Getting hired for a data annotation role generally requires basic computer skills, attention to detail, and sometimes familiarity with specific tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible, though competition can vary based on the employer and location.

What are the key skills and qualifications needed to thrive in the Data Annotation position, and why are they important?

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

What does a data annotator do?

A data annotator labels and tags data such as images, text, or videos to help machine learning models understand and learn from the data. They use tools and follow guidelines to ensure accuracy and consistency, often working with large datasets in a structured environment. Attention to detail and knowledge of annotation tools are important for this role.
What are the most commonly searched types of Data Annotation jobs in Texas? The most popular types of Data Annotation jobs in Texas are:
What are popular job titles related to Data Annotation jobs in Texas? For Data Annotation jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Annotation jobs in Texas look for? The top searched job categories for Data Annotation jobs in Texas are:
What cities in Texas are hiring for Data Annotation jobs? Cities in Texas with the most Data Annotation job openings:
Data Annotation jobs near you
Infographic showing various Data Annotation job openings in Texas as of June 2026, with employment types broken down into 40% Full Time, 20% Part Time, and 40% Contract. Highlights an 40% In-person, and 60% Remote job distribution, with an average salary of $46,160 per year, or $22.2 per hour.
Data Annotation Specialist

Data Annotation Specialist

Saronic Technologies

Austin, TX • On-site

Contractor

Posted 11 days ago

Job description

Saronic Technologies is a leader in revolutionizing autonomy at sea, dedicated to developing state-of-the-art solutions that enhance maritime operations through autonomous and intelligent platforms.
Job Overview
We are seeking a Data Annotation Specialist to annotate and review visual datasets used to train and evaluate machine-learning models for maritime perception and autonomy. This role supports our software, perception, and autonomy teams by ensuring labeled data is accurate, consistent, and useful for model development.
The ideal candidate has prior computer vision annotation experience, strong visual attention to detail, and the ability to maintain speed and accuracy through repetitive labeling work. This person should be comfortable following detailed instructions, adapting as labeling rules change, and supporting a fast-moving technical team.
This is an on-site, full-time contract role with an intended path to full-time conversion based on performance and business needs. Upon conversion, the employee would be eligible for Saronic's standard full-time benefits. This position reports to the Data Annotation Manager.
Responsibilities
  • Annotate and review large volumes of image, video, infrared, and other sensor data using computer vision labeling methods.
  • Identify vessels, objects, environmental features, and other elements relevant to maritime autonomy.
  • Maintain accuracy, consistency, and productivity across repetitive, detail-heavy datasets.
  • Apply evolving labeling guidelines and escalate unclear edge cases when needed.
  • Perform both manual annotation work and quality review of auto-labeled data as needed.
  • Willingness to support priority project deadlines when needed.
Qualifications
  • Prior experience in computer vision data annotation or labeling.
  • Familiarity with annotation tools such as Labelbox, CVAT, or similar
  • Experience with annotation types such as segmentation masks, bounding boxes, key points, object tracking, or classification.
  • Strong visual pattern recognition, spatial reasoning, and attention to detail.
  • Comfortable performing repetitive, process-driven work for extended periods while maintaining quality.
  • Able to adapt to changing project priorities, labeling rules, and quality standards in a fast-paced environment.
  • Strong communication skills and willingness to ask questions, accept feedback, and collaborate with the team.
  • Basic understanding of maritime environments, autonomous systems, robotics, or defense technology is a plus.

Saronic CCPA Notice for Candidates and California Employees
If this role is based in the United States, it requires access to export-controlled information or items that require "U.S. Person" status. As defined by U.S. law, individuals who are any one of the following are considered to be a "U.S. Person": (1) U.S. citizens, (2) legal permanent residents (a.k.a. green card holders), and (3) certain protected classes of asylees and refugees, as defined in 8 U.S.C. 1324b(a)(3).
Saronic does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits. We are also committed to providing reasonable accommodations for qualified individuals with disabilities.

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