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Freelance English Remote Annotator

Posted 7 days ago
All others
Freelance
USA

Overview

DataForce by TransPerfect is seeking freelance English (US) Annotators to participate in an innovative project related to Artificial Intelligence, focusing on generating detailed descriptions of human speech attributes.

In Short

  • Flexible schedule with a preferred weekly availability of 20 hours or more.
  • Engagement model as a freelance/independent contractor.
  • Work location is remote, from anywhere in the United States.
  • Project duration until the end of May with potential for extension.
  • Responsibilities include listening to audio recordings and describing speech attributes.
  • Idiomatic fluency in English (US) is required.
  • Excellent writing and grammar skills are essential.
  • Ability to work independently and meet deadlines.
  • Attention to detail and delivering error-free work is crucial.
  • Familiarity with online annotation/transcription tools is preferred.

Requirements

  • Fluency in English (US).
  • Strong writing and grammar skills.
  • Independence and reliability in meeting deadlines.
  • Ability to adhere to project guidelines.
  • High attention to detail.
  • Minimum availability of 20 hours per week.
  • Preferred experience with annotation tools.

Benefits

  • Opportunity to work on an innovative AI project.
  • Flexible working hours.
  • Remote work from anywhere in the United States.
  • Potential for project extension.
  • Be part of a global company with a focus on language and technology solutions.
TransPerfect logo

TransPerfect

TransPerfect is the world’s largest provider of language and technology solutions for global business, with a presence in over 100 cities worldwide. The company offers high-quality data for Human-Machine Interaction, catering to some of the most prestigious technology companies. Their DataForce division specializes in gathering, enriching, and processing data for Machine Learning across various AI domains, ensuring the development of advanced machine learning systems such as neural networks and generative models.

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