AI Data Quality Specialist - English (Philippines)
Company shown to members 🔒 · Remote · Philippines only
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First recorded by Psst: 2 November 2026. Your first 3 jobs are free to apply to (the first right away, 2 more with your email). After that, the company and the apply link are for Psst members, from $4.99 for 7 days.
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The 20-second read
- Experience
- Experience not stated
- Where you can live
- Philippines only
- Languages
- English
- Job type
- Contract or freelance
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Job details
- Where you can work
- Philippines
- Employment type
- Contract
- Advertised pay
- $4.5/hr
- Experience
- Experience not stated
- Employer publication date
- 10 March 2026
- First recorded by Psst
- 2 November 2026
- Last checked at the source
- 10 November 2026
About the job
Contract Type: Freelance
Language: English (Philippines)
About the Role
We are seeking a detail-oriented AI Data Quality & Annotation Specialist to help develop and evaluate large language models (LLMs). Your role will involve reviewing English language content to assess sentiment accuracy, factual consistency, and reasoning quality using structured guidelines. This position is ideal for individuals with sharp analytical skills, attention to detail, and the ability to consistently apply labeling standards.
What You Will Do
- Review and label content for sentiment, factual accuracy, and reasoning issues.
- Evaluate model outputs across quality dimensions using scoring frameworks.
- Validate automated assessments and identify discrepancies or errors.
Requirements
- Advanced English proficiency (reading and writing) with professional-level fluency.
- Strong comprehension and articulation skills, with the ability to provide clear and well-reasoned written justifications.
- Previous experience in data annotation, AI training, or related projects.
- Preferred experience in analytical fields such as linguistics, journalism, research, or similar domains.
- Exceptional attention to detail and accuracy.
- Proven analytical reasoning and critical thinking abilities.
- Consistency in decision-making across high volumes of tasks.
- Familiarity with AI systems, large language models (LLMs), or evaluation processes (preferred but not required).
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