Validator – RLHF (Reinforcement Learning with Human Feedback) Initiative

 Posted 2 months ago
  
 Kenya
  
10+ years experience
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AI Summary

The Validator will conduct final quality assurance on agricultural Q&A content to ensure it meets the Golden Q-A framework standards. They are responsible for validating approximately 2,000 Q&A pairs per month and providing actionable feedback to improve content generation processes.

About Digital Green

Digital Green is a global development organization that empowers smallholder farmers through digital solutions, data, and partnerships. We work at the intersection of technology and agriculture to improve livelihoods, enhance climate resilience, and promote inclusive agricultural systems.

Background

Digital Green is implementing the RLHF (Reinforcement Learning with Human Feedback) initiative to enhance the quality, reliability, and contextual relevance of agricultural advisory content. This initiative leverages a combination of AI systems, human expertise, and structured frameworks to generate high-quality question-and-answer (Q&A) content for farmers and extension workers.

To ensure excellence in content quality, we are recruiting experienced Validators to serve as the final quality assurance layer for reviewed Q&A outputs.

Position Summary

The Validator will be responsible for conducting final quality assurance of agricultural Q&A content, ensuring it meets Digital Green’s Golden Q-A framework standards. The role requires strong technical expertise, critical analysis, and a deep understanding of agricultural systems, climate resilience, and gender inclusion.

Key Responsibilities

  • Conduct final validation of Q&A pairs following the review stage
  • Assess content against validation criteria, including:
    • Technical accuracy
    • Contextual relevance
    • Clarity and usability for farmers
    • Alignment with gender and climate considerations
  • Confirm that reviewer feedback has been properly incorporated
  • Flag inaccuracies, inconsistencies, or gaps requiring revision
  • Provide validation decisions (approve, revise, reject) using designated tools
  • Participate in pilot/testing phases and provide feedback on workflows
  • Maintain accurate records through the project dashboard
  • Collaborate with reviewers and project teams to ensure consistent quality standards

Areas of Expertise

Applicants should have demonstrated expertise in one or more of the following:

  • Livestock Sciences
  • Climate-smart agriculture and resilience
  • Gender and social inclusion in agriculture
  • Agricultural extension and advisory services

Key Deliverables

  • Validate approximately 2,000 Q&A pairs per month
  • Document validation decisions via the project system
  • Produce monthly validation reports (progress, insights, recommendations)
  • Provide feedback to improve content generation and review processes
  • Deliver high-quality, approved Q&A content for integration into digital advisory systems

Qualifications and Experience

  • Degree (or higher) in Agriculture, Livestock Sciences, Climate Science, Gender Studies, Agricultural Extension, or a related field
  • Minimum 8-10 years of relevant professional experience
  • Strong understanding of climate-smart agriculture and gender-responsive approaches
  • Experience reviewing or validating technical agricultural content
  • Familiarity with AI-generated or digital content is an added advantage
  • Excellent analytical, documentation, and reporting skills

Reporting Line

The Validator will report to the Project Head, Golden Q-A / RLHF Workstream and collaborate closely with reviewers and project teams.

Core Competencies

  • Attention to detail and quality assurance
  • Strong critical thinking and problem-solving skills
  • Ability to work independently and meet deadlines
  • Effective communication and collaboration skills
  • Commitment to inclusive and farmer-centered content

Equal Opportunity Statement
Digital Green is an equal opportunity employer committed to diversity and inclusion. We encourage applications from qualified candidates regardless of gender, disability, or background.



 

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