Torchora
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Key Responsibilities and Required Skills for Verification Trainer

💰 $65,000 - $95,000

AI TrainingData AnnotationQuality AssuranceFact-CheckingEducation & Training

🎯 Role Definition

We are searching for a highly skilled and detail-oriented Verification Trainer to join our dynamic team. In this critical role, you will be at the forefront of ensuring the integrity and accuracy of the data that powers our advanced AI and Large Language Models (LLMs). You will be responsible for designing, developing, and delivering comprehensive training programs to our data annotators and verification specialists. Your expertise will directly influence the quality of our model's outputs, its ability to perform nuanced fact-checking, and its adherence to safety guidelines. This is a unique opportunity to contribute to the responsible development of cutting-edge AI by empowering the human experts who train it.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Content Reviewer / Content Moderator
  • Fact-Checker or Research Assistant
  • Quality Assurance Analyst
  • Data Annotator / AI Trainer

Advancement To:

  • Senior Verification Trainer
  • Training Program Manager
  • Quality Assurance Lead
  • Team Lead, Verification Operations

Lateral Moves:

  • AI Policy Specialist
  • Quality Operations Analyst
  • Content Strategist

Core Responsibilities

Primary Functions

  • Design and develop comprehensive training curricula and instructional materials focused on advanced verification techniques, fact-checking methodologies, and content policy application.
  • Deliver engaging and effective training sessions, workshops, and one-on-one coaching to new and existing verification specialists and data annotators, both in-person and remotely.
  • Evaluate the effectiveness of training programs through performance metrics, quality scores, and feedback, continuously iterating on content to improve learning outcomes.
  • Create and maintain a detailed knowledge base, including Standard Operating Procedures (SOPs), guidelines, and best practice documentation for all verification tasks.
  • Conduct regular Quality Assurance (QA) audits on the work of verification teams to identify knowledge gaps, performance trends, and areas for targeted re-training.
  • Mentor and guide team members on complex and ambiguous verification cases, acting as the subject matter expert for nuanced policy interpretation and source evaluation.
  • Analyze and deconstruct complex topics across a wide range of domains (e.g., science, history, current events) to create clear, concise, and verifiable training examples.
  • Collaborate closely with policy and engineering teams to understand changes in guidelines or tools, and swiftly develop and deploy updated training modules to the verification workforce.
  • Develop robust assessment tools, including quizzes, practical exercises, and certification programs, to accurately measure trainee comprehension and readiness.
  • Stay abreast of emerging trends in misinformation, disinformation, and digital media literacy to ensure training content remains relevant and effective.
  • Provide detailed, constructive feedback to individuals on their verification performance, helping them improve accuracy, efficiency, and critical thinking skills.
  • Lead "train-the-trainer" sessions to scale training efforts and empower team leads and senior specialists to become effective mentors.
  • Analyze qualitative and quantitative data from verification tasks to identify systemic issues and provide actionable insights to improve overall data quality and model performance.
  • Create specialized training modules for new project verticals or complex data types, ensuring teams are equipped to handle evolving verification requirements.
  • Facilitate calibration sessions among verification specialists to ensure consistent application of quality standards and policy guidelines across the team.
  • Partner with project managers to forecast training needs for new hires and ongoing projects, ensuring seamless onboarding and continuous skill development.
  • Investigate and document root causes of quality errors, developing and implementing corrective action plans and preventative training measures.
  • Act as a primary point of contact and subject matter expert for escalations related to content policy, fact-checking disputes, and source credibility assessments.
  • Develop and implement strategies for improving the critical thinking and online research skills of the verification team, promoting a culture of deep inquiry and skepticism.
  • Generate and present regular reports on training progress, team quality metrics, and the overall health of the verification process to stakeholders and leadership.
  • Champion a culture of continuous learning and quality excellence within the verification and data annotation teams.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis to identify quality trends.
  • Contribute to the organization's data strategy and roadmap, particularly regarding human-in-the-loop quality control.
  • Collaborate with product and business units to translate data quality needs into engineering and training requirements.
  • Participate in sprint planning and agile ceremonies within the data operations team.
  • Assist in the user acceptance testing (UAT) of new annotation tools and platforms.
  • Document and escalate technical issues or tool-related feedback from the verification team to the appropriate engineering groups.

Required Skills & Competencies

Hard Skills (Technical)

  • Expert-level proficiency in online research, source vetting, and advanced fact-checking techniques.
  • Experience with data annotation, content review, or quality assurance platforms.
  • Strong understanding of Large Language Models (LLMs) and the principles of AI training and evaluation.
  • Ability to analyze and interpret both qualitative and quantitative data to drive decision-making.
  • Proficiency in developing instructional materials, including presentations, guides, and e-learning modules.
  • Familiarity with Learning Management Systems (LMS) and other training delivery technologies.
  • Competency with spreadsheet software (e.g., Excel, Google Sheets) for data tracking and analysis.
  • Knowledge of content policy, safety guidelines, and trust & safety principles in a digital environment.
  • Experience in creating and running Quality Assurance (QA) programs and calibration sessions.
  • Strong command of English grammar, syntax, and style for creating clear and unambiguous documentation.
  • Basic understanding of project management principles and agile methodologies.

Soft Skills

  • Exceptional Critical Thinking & Analytical Skills
  • Impeccable Attention to Detail and Accuracy
  • Excellent Written and Verbal Communication
  • Patience, Empathy, and Mentoring Abilities
  • Strong Problem-Solving and Decision-Making Skills
  • Adaptability and Resilience in a Fast-Paced Environment
  • High Degree of Intellectual Curiosity and Eagerness to Learn
  • Objectivity and the Ability to Mitigate Personal Bias
  • Strong Organizational and Time Management Skills
  • Collaborative Team Player with Strong Interpersonal Skills

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's Degree or equivalent practical experience in a research-intensive field.

Preferred Education:

  • Master's Degree in a related field.

Relevant Fields of Study:

  • Journalism
  • Library Science / Information Science
  • Linguistics
  • Education
  • Communications
  • History or other research-intensive humanities/social sciences

Experience Requirements

Typical Experience Range: 3-5+ years of experience in a relevant role.

Preferred: Direct experience in training, quality assurance, fact-checking, or content moderation for tech companies, AI development, or media organizations. Proven track record of developing and delivering successful training programs.

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