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Online Data Labelling Jobs (NOW HIRING)

Doppel Inc

Workflow Operations Manager - Labeling

$120K - $135K/yr

They will oversee the teams responsible for alert triage, operational decision-making, data ... online fraud before attacks can spread. Our Threat Grid turns every customer signal into shared ...

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All JobsOnline Data Labelling Jobs

Online Data Labelling information

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$46K

$165K

$243.5K

How much do online data labelling jobs pay per year?

As of Jun 21, 2026, the average yearly pay for online data labelling in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is the difference between Online Data Labelling vs Data Annotation?

AspectOnline Data LabellingData Annotation
CredentialsBasic computer skills, attention to detailSimilar, often no formal certification required
Work EnvironmentRemote, flexibleRemote or in-office, depending on project
Industry UsageCommon in AI/ML data preparationUsed across AI, computer vision, NLP projects
Search IntentOnline Data Labelling vs Data Annotation

Online Data Labelling and Data Annotation are closely related roles in AI data preparation. While both involve labeling data for machine learning, Online Data Labelling often emphasizes quick, online tasks, whereas Data Annotation may include more detailed, specialized labeling. Both roles are essential in training AI models and share similar skills and work environments.

What is online data labelling?

Online data labelling is the process of tagging or annotating data—such as images, text, or audio—using digital tools to make it understandable for machine learning algorithms. Data labelers review raw data and apply predefined labels to help train artificial intelligence systems, enabling them to recognize patterns and make predictions. This work is essential for improving the accuracy and performance of AI models in various applications, such as image recognition, natural language processing, and autonomous vehicles. Online data labelling jobs are often remote and require attention to detail, consistency, and sometimes domain-specific knowledge.

What are some common challenges faced by online data labelers, and how can they be managed effectively?

Online data labelers often encounter challenges such as repetitive tasks, strict accuracy requirements, and tight deadlines. Maintaining high attention to detail is crucial, as even small errors can impact the quality of machine learning models. To manage these challenges, it's helpful to take regular breaks, use productivity tools, and communicate any ambiguities or unclear instructions with supervisors or team leads. Many organizations also offer support channels and quality assurance feedback to help labelers continuously improve their work.

What are the key skills and qualifications needed to thrive as an Online Data Labeller, and why are they important?

To excel as an Online Data Labeller, you need strong attention to detail, basic data handling skills, and familiarity with data annotation protocols, often requiring at least a high school diploma. Proficiency with data labelling platforms such as Labelbox, Supervisely, or Scale AI, and sometimes knowledge of spreadsheet tools, is typically necessary. Reliability, consistency, and the ability to follow detailed guidelines make individuals stand out in this role. These skills ensure high-quality, accurately labelled datasets that are critical for training effective AI and machine learning models.
More about Online Data Labelling jobs
What cities are hiring for Online Data Labelling jobs? Cities with the most Online Data Labelling job openings:
What are the most commonly searched types of Data Labelling jobs? The most popular types of Data Labelling jobs are:
What states have the most Online Data Labelling jobs? States with the most job openings for Online Data Labelling jobs include:
Online Data Labelling jobs near you
Infographic showing various Online Data Labelling job openings in the United States as of June 2026, with employment types broken down into 84% Full Time, and 16% Part Time. Highlights an 78% Physical, 1% Hybrid, and 21% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Search and Data Labelling Rater - German

Search and Data Labelling Rater - German

Welo Data

Austin, TX • Remote

Part-time

Posted yesterday

Job description

We are looking for detail-oriented Search & Data Labeling Raters specifically - German Language to support an AI data annotation project focused on improving e-commerce search experiences. In this role, you will evaluate the relevance of search results by analyzing customer queries and matching them with appropriate products. Your work will directly contribute to enhancing search quality and overall user experience.

Key Responsibilities:
  • Analyze and understand the intent behind customer search queries
  • Identify product types (PT) and relevant attributes (e.g., brand, size, color) within queries
  • Evaluate the relevance between search queries and product listings using defined guidelines (ESCI framework)
  • Determine product availability and validate product links
  • Provide accurate, consistent, and high-quality annotations
  • Follow project guidelines and meet productivity and quality benchmarks

Project Details:

  • Start Date: ASAP
  • Duration: 4 weeks
  • Task Type: AI Data Annotation 
  • Job Type: Freelance contract
  • Pay Rate: $7 USD/hour
  • Location: Remote

Requirements:

  • Strong analytical and comprehension skills
  • Ability to understand e-commerce search behavior
  • High attention to detail and accuracy
  • Basic understanding of online shopping platforms
  • Proficiency in the required language
  • Ability to follow detailed guidelines and work independently

Join our team and help shape the future of AI communication!

$7 - $7 an hour

Why Join Welo Data?  

✨ Limitless Flexibility  

Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.   

🌱 Limitless Growth  

Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.   

🌍 Limitless Support  

Be part of a global contributor community with responsive guidance and support.   

💡 Real Impact  

Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.  

How to Apply? 

Apply now by answering a few quick questions to join our database and become part of our growing community. 

About Welo Data 

Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.  

At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms. 

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.