AI Trainer

1 day ago

Greater Kuala Lumpur, Malaysia Risewave Consulting, Inc. Full time 90,000 - 120,000 per year

Key Responsibilities

  • Conduct comprehensive onboarding sessions for new annotators, ensuring a strong understanding of tools, workflows, and rubrics.
  • Design, update, and deliver training materials, SOPs, and reference guides aligned with evolving project needs.
  • Lead refresher and calibration sessions to address performance gaps and incorporate rubric updates.
  • Develop assessment tests and evaluation forms to measure annotator readiness prior to production deployment.
  • Review performance reports with QA and PM teams regularly to identify training and skill development needs.
  • Coach underperforming annotators through one-on-one mentoring and targeted improvement plans.
  • Track learning progress, document outcomes, and maintain accurate training compliance records.
  • Partner with QA teams to analyze recurring error patterns and implement effective training solutions.
  • Ensure annotators consistently meet performance KPIs (Accuracy ≥90%, Consistency ≥95%, Rejection Rate ≤10%).
  • Participate in guideline calibration and contribute to improving annotation clarity and usability.
  • Drive continuous improvement initiatives through innovative and visual learning approaches.
  • Act as the communication bridge between Project Management, Quality Assurance, and Operations.
  • Support new project rollouts by developing and implementing trainer-led readiness programs.

Qualifications

Required:

  • Bachelor's degree in STEM, Education, Data Science, Psychology, Linguistics, or related field.
  • 2–4 years of experience in training, quality assurance, or performance management within BPO, AI annotation, or data operations.
  • Strong presentation, communication, and coaching abilities.
  • Proven track record in analyzing performance data and executing structured training interventions.
  • Familiarity with productivity and project management tools (e.g., Airtable, Smartsheet, Jira).

Preferred:

  • Experience in AI data labeling, machine learning operations, or LLM annotation environments.
  • Understanding of quality assurance frameworks and process improvement methodologies.
  • Certification in Six Sigma Green Belt, Kaizen, or Train-the-Trainer (TTT).
  • Knowledge of data accuracy metrics and QA rubrics related to AI or linguistic projects.

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