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Data Annotator - Freelance


Toloka AI

Job Description

Annotation drives AI’s capabilities.

Industries across the board are embracing AI, and the backbone of this revolution is accurate data labeling (data annotation). As an AI Tutor - Expert Annotator, you will not just be performing routine tasks; you are a meticulous specialist ensuring the highest quality of data markup. In this role, you help pave the way for more reliable and responsible AI models by laying the groundwork through precise annotation.


  • Accurately label and annotate data following comprehensive project guidelines.
  • Make justified decisions on ambiguous content by applying critical thinking to preserve the integrity of the dataset.
  • Actively collaborate with team members to discuss and resolve ambiguities, align on best practices, and enhance project outcomes.
  • Consistently adhere to established data labeling standards and protocols, ensuring the highest quality and reliability of data.


Our ideal candidate:

  • Has great command of English: advanced (C1) / proficiency (C2) / native level.
  • Has a keen eye for detail: precision is paramount in data labeling.
  • Is a dedicated performer who recognizes the importance of even routine tasks.


  • Be part of a significant project for a leading technology company, making a substantial impact on the future of AI.
  • Enjoy the flexibility of a part-time, remote role that accommodates your schedule.
  • Try your hand at an AI project and enrich your portfolio with new experiences.

Advice from our career coach

As an AI Tutor - Expert Annotator, your role is crucial in ensuring the accuracy and reliability of data labeling for AI models. To stand out as an applicant for this position, keep in mind the following:

  • Highlight your English proficiency level (advanced/ proficiency/ native) to showcase your ability to accurately label data.
  • Emphasize your attention to detail and precision when it comes to data annotation tasks.
  • Demonstrate your critical thinking skills in making justified decisions on ambiguous content to maintain dataset integrity.
  • Showcase your ability to collaborate effectively with team members to enhance project outcomes.
  • Illustrate your commitment to adhering to data labeling standards and protocols for ensuring data quality and reliability.

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