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Annotation Labelling Jobs in Texas (NOW HIRING)

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Annotation Labelling information

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What are the key skills and qualifications needed to thrive as an annotation labelling specialist?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by annotation labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

What is the difference between Annotation Labelling vs Data Labeling Specialist?

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

What are popular job titles related to Annotation Labelling jobs in Texas?

For Annotation Labelling jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Annotation Labelling jobs in Texas look for?

The top searched job categories for Annotation Labelling jobs in Texas are:

What cities in Texas are hiring for Annotation Labelling jobs?

Cities in Texas with the most Annotation Labelling job openings:

Annotation Labelling jobs near you

Freelance Annotator (English) - AI Trainer

Mindrift - Data annotation

Austin, TX • Remote

$20/hr

Part-time

Re-posted 18 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.

Apply