Profile of NUR AFIQAH BINTI AWANG NASRAN

NUR AFIQAH BINTI AWANG NASRAN AI Generalist Evaluator
1 year experience 0 projects worked Malaysia
RM25.00 /hr RM0 earned
AI TrainerCreative writing

I help AI teams improve model quality through high-quality data annotation, evaluation, and human feedback.

What I do:

  • Data Annotation & Labeling – Adding structured tags, labels, and metadata to text, images, audio, and video so AI systems can learn effectively.
  • AI Output Evaluation & Ranking – Comparing and ranking multiple model responses by accuracy, helpfulness, truthfulness, and safety. I flag hallucinations, bias, and other issues with clear reasoning.
  • RLHF (Reinforcement Learning from Human Feedback) – Rating and comparing AI outputs to provide the human feedback that trains safer, more accurate models.
  • Hallucination & Bias Detection – Carefully spotting factually incorrect or fabricated content and identifying systematic biases in model outputs.
  • Transcription & Audio Review – Converting speech to text with high accuracy, proper formatting, and speaker identification, followed by quality checks.

My strengths:

  • Strong attention to detail and ability to follow complex rubrics and instructions
  • Clear, professional English writing for structured feedback (150–300 words per item)
  • Experience handling ambiguity and edge cases with explicit assumptions
  • Consistent quality and fast turnaround (targeting 98%+ acceptance rate)

I am currently seeking generalist AI evaluator, data annotator, and RLHF roles on Mercor and similar platforms.

Work History (0)

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Work Experiences

  • Generalist AI Evaluator

    Oneforma (Centific)

    November 2025 - Now

    I help AI teams improve model quality through high-quality data annotation, evaluation, and human feedback.
    What I do:
    Data Annotation & Labeling – Adding structured tags, labels, and metadata to text, images, audio, and video so AI systems can learn effectively.
    AI Output Evaluation & Ranking – Comparing and ranking multiple model responses by accuracy, helpfulness, truthfulness, and safety. I flag hallucinations, bias, and other issues with clear reasoning.
    RLHF (Reinforcement Learning from Human Feedback) – Rating and comparing AI outputs to provide the human feedback that trains safer, more accurate models.
    Hallucination & Bias Detection – Carefully spotting factually incorrect or fabricated content and identifying systematic biases in model outputs.
    Transcription & Audio Review – Converting speech to text with high accuracy, proper formatting, and speaker identification, followed by quality checks.
    My strengths:
    Strong attention to detail and ability to follow complex rubrics and instructions
    Clear, professional English writing for structured feedback (150–300 words per item)
    Experience handling ambiguity and edge cases with explicit assumptions
    Consistent quality and fast turnaround (targeting 98%+ acceptance rate)
    I am currently seeking generalist AI evaluator, data annotator, and RLHF roles on Mercor and similar platforms.