αfrisync ⍺𝓲 Enterprise

AI data annotator

$1,500 – $3,500/h Contract Remote
Attention to detailInstruction followingLanguage and comprehension skillsAnalytical thinkingBasic technical literacyConsistencyTime managementFocus and patienceCommunication skillsAdaptability

A Data Annotator is responsible for labeling, tagging, and structuring data used to train machine learning and artificial intelligence systems. This role ensures that raw data is accurately transformed into high-quality datasets that improve model performance in areas such as language processing, computer vision, speech recognition, and recommendation systems.

Core Responsibilities

  • Label and annotate text, images, audio, or video data according to defined guidelines
  • Classify content based on categories, sentiment, intent, or other attributes
  • Transcribe or correct text from audio recordings when required
  • Identify objects, entities, or patterns in datasets
  • Ensure consistency and accuracy across large volumes of data
  • Follow annotation guidelines and update feedback when rules evolve
  • Collaborate with quality assurance teams to fix errors and improve dataset quality

Required Skills

  • Strong attention to detail and accuracy
  • Basic understanding of data labeling tools or willingness to learn them
  • Ability to follow structured instructions carefully
  • Good reading comprehension and language skills
  • Consistency in applying rules across repetitive tasks
  • Basic computer literacy and typing skills

Preferred Qualifications

  • Experience with data labeling platforms (e.g., CVAT, Labelbox, Prodigy, or similar tools)
  • Familiarity with AI/ML concepts is an advantage but not required
  • Experience in transcription, translation, or content moderation is a plus
  • Ability to work with multiple languages is beneficial

Key Competencies

  • Precision and consistency
  • Focus and patience for repetitive tasks
  • Analytical thinking for classification decisions
  • Time management and productivity
  • Ability to work independently or in teams

Work Output Examples

  • Bounding boxes for images (e.g., identifying objects in photos)
  • Sentiment labels for text (positive, neutral, negative)
  • Entity tagging in sentences (names, locations, organizations)
  • Speech-to-text transcription corrections
  • Content moderation flags

Ideal Candidate Profile

The ideal Data Annotator is detail-oriented, disciplined, and able to maintain high accuracy under repetitive workloads. They should be comfortable following strict guidelines and contributing to the development of high-quality AI training datasets.

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