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Part Time Remote Data Labelling Jobs in Dallas, TX

This part-time remote opportunity is ideal for creative professionals with hands-on experience in ... Translate complex data into clear visual storytelling with a strong focus on minimalism and precise ...

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Part Time Remote Data Labelling information

See Dallas, TX salary details

$45.5K

$163.2K

$240.9K

How much do part time remote data labelling jobs pay per year?

As of Jul 4, 2026, the average yearly pay for part time remote data labelling in Dallas, TX is $163,241.00, according to ZipRecruiter salary data. Most workers in this role earn between $132,100.00 and $168,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Part Time Remote Data Labelling specialist, and why are they important?

To excel as a Part Time Remote Data Labelling specialist, you need strong attention to detail, basic computer literacy, and a solid understanding of data privacy and handling protocols, often requiring a high school diploma or equivalent. Familiarity with annotation platforms, spreadsheet software, and sometimes specific data labelling tools like Labelbox or Supervisely is typically required. Reliability, time management, and clear communication are crucial soft skills for meeting deadlines and collaborating in a remote setting. These skills and qualities ensure that labelled data is accurate, consistent, and valuable for training effective machine learning models.

What is the difference between Part Time Remote Data Labelling vs Part Time Remote Data Annotation?

AspectPart Time Remote Data LabellingPart Time Remote Data Annotation
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAI, machine learning, data processingAI, machine learning, data processing
Job FocusLabeling data for training AI modelsAnnotating data for AI training

Part Time Remote Data Labelling and Part Time Remote Data Annotation are similar roles involving preparing data for AI systems. Labelling typically involves categorizing data, while annotation may include adding detailed notes or markings. Both roles require attention to detail and are performed remotely, making them suitable for flexible schedules. The main difference lies in the specific tasks, but they are often used interchangeably depending on the employer or project.

What is a part time remote data labelling job?

A part time remote data labelling job involves annotating or tagging data—such as images, text, or audio—from your own location, typically using specialized software provided by employers. The role is essential for training machine learning models, as accurate labels help computers learn to recognize patterns. These jobs are often flexible, allowing you to set your own hours and work from anywhere with an internet connection. No advanced technical skills are usually required, but attention to detail is important.

What are some common challenges faced by part-time remote data labelling professionals, and how can they be managed?

Part-time remote data labellers often face challenges such as maintaining consistent accuracy, staying focused during repetitive tasks, and managing communication with a distributed team. To address these, it’s helpful to establish a quiet, distraction-free workspace, use productivity techniques like the Pomodoro method, and regularly review labelling guidelines to minimize errors. Leveraging communication tools and participating in team check-ins can also help clarify questions and build a sense of connection with colleagues.
What are the most commonly searched types of Remote Data Labelling jobs in Dallas, TX? The most popular types of Remote Data Labelling jobs in Dallas, TX are:
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What cities near Dallas, TX are hiring for Part Time Remote Data Labelling jobs? Cities near Dallas, TX with the most Part Time Remote Data Labelling job openings:

AI Trainer - Freelance Data Annotator

Toloka Annotators

Dallas, TX • Remote

$23/hr

Part-time

Posted 24 days ago


Job description

Please submit your resume in English and indicate your level of English.

At Toloka, we connect smart, curious people from around the world with freelance online tasks that train and improve artificial intelligence.

What we do

The Toloka Annotators connects individuals with Generative AI projects from leading tech innovators. Our mission is to unlock the full potential of AI by involving real people from around the world in the development process.

About the Role

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.

Responsibilities:

  • 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

Important note: This is project-based work. Tasks are available only when projects are active. You may be invited to one or more projects depending on your profile and current opportunities.

Each project has its own compensation level based on scope and expertise required. On this project, AI trainers earn up to $23 per hour equivalent.

Requirements

  • Bachelor's degree in any discipline
  • Minimum 1 year of experience in any professional role
  • Advanced level of English (C1 or higher), both written and spoken
  • 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

Benefits

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.
  • Work on advanced AI projects and gain valuable experience that enhances your portfolio.
  • Influence how future AI models understand and communicate in your field of expertise.