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Data Annotation For Ai Jobs in Texas (NOW HIRING)

YO AI Labs

AI Software Engineer Expert - Remote

Dallas, TX · Remote

$100 - $200/hr

Analyze, review, and improve AI-generated software engineering content for technical accuracy and ... Data Annotation * Fact Checking * Independent Research * Business Communication * Problem-Solving

UNAVAILABLE

AI Data Engineer

Frisco, TX · On-site

$140 - $210/hr

ApplyMLOpsandDataOpsbest practices for orchestration, testing, deployment, monitoring, and lineage ... Data annotation best practices with CVAT,Roboflow, and Label Studio, including model-assisted ...

micro1 AI

AI Trainer - Microbiology Expert

Pasadena, TX · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

micro1 AI

AI Trainer - Microbiology Expert

Waco, TX · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

micro1 AI

AI Trainer - Microbiology Expert

Denton, TX · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

micro1 AI

AI Trainer - Microbiology Expert

Austin, TX · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

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All JobsData Annotation For Ai JobsData Annotation For Ai Jobs in Texas

Data Annotation For Ai information

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.

What are the key skills and qualifications needed to thrive as a data annotation specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What is the difference between Data Annotation For Ai vs Data Labeler?

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

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Data Annotation For Ai jobs near you
Infographic showing various Data Annotation For Ai job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 11% Part Time, 4% Contract, and 1% Nights. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

AI Trainer - Freelance Data Annotator

Mindrift - Data annotation

Houston, TX • Remote

$20/hr

Part-time

Re-posted 20 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