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100 years and 56 days since the five-day weekRead the story

Lingala Bilingual Expert

Part time$45 - $95/hrRemote · USA

Pay: $45-$95 per hour (USD).

Job Title: Lingala Bilingual Expert

Job Type: Contractor

Location: Remote

Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Key Responsibilities:

  1. Transcribe video content in Lingala, ensuring accurate and detailed capture of spoken language.
  2. Clearly outline timestamps and describe the emotional tone and intent of speakers.
  3. Analyze and evaluate grammar, tone, and overall language structure in both Lingala and English content.
  4. Define and elaborate on the conceptual aspects of words and phrases, capturing cultural and contextual nuances.
  5. Perform complex language tasks to train and fine-tune AI language models.
  6. Collaborate with the customer's team to ensure deliverables meet quality standards and project requirements.
  7. Commit to at least 15 hours of focused work per week, maintaining consistency in quality and detail.

Required Skills and Qualifications:

  1. Native or near-native proficiency in both Lingala and English, with advanced written and verbal communication skills.
  2. Exceptional attention to detail in linguistic analysis and transcription work.
  3. Demonstrated ability to identify and articulate emotional nuances and tone in spoken language.
  4. Strong analytical and critical thinking skills applied to language tasks.
  5. Experience in transcription, translation, localization, or similar linguistics-focused roles.
  6. Ability to work independently and collaborate effectively within a remote environment.
  7. Reliable commitment to a minimum of 15 hours per week.

Preferred Qualifications:

  1. Background in linguistics, language education, or related fields.
  2. Experience working on AI, NLP, or data annotation projects.
  3. Familiarity with best practices in high-quality transcription and annotation.