AI Trainer Lead - Model Evaluation

YO IT Consulting; Dubai; On-site; AED 111,600 - 178,560; Full time

Job summary

YO IT Consulting in Dubai seeks an AI Trainer Lead to evaluate model responses and annotate datasets. You will apply rubrics, score reasoning quality, and provide precise, actionable feedback to improve AI training workflows.

The role requires strong analytical skills and meticulous judgment in a fully remote, contract-based setting. Ideal candidates have a Bachelor's degree and proven experience evaluating large content volumes with high accuracy and clear documentation.

Qualifications

• Bachelor's degree from a recognized institution.
• Experience evaluating or scoring substantial volumes of content against detailed criteria.
• Strong attention to detail and a commitment to accuracy.

Responsibilities

• Evaluate AI-generated responses using defined rubrics, scoring criteria, and project metrics.
• Assess answers for factual accuracy, relevance, coherence, and instruction compliance.
• Annotate, categorize, label, and review datasets used for AI model training and evaluation.
• Identify hallucinated facts, unsupported conclusions, contradictions, and bias.
• Provide clear written explanations supporting evaluation scores and ranking decisions.

Skills

Attention to detail

English communication

Critical reading

Analytical reasoning

Data annotation

Model evaluation

Remote collaboration

Documentation

Rubric interpretation

Quality assurance

Education

Bachelor's degree

Tools

Annotation tools

Evaluation platforms

Quality trackers

Job description

AI Trainer Lead - Model Evaluation in Dubai, United Arab Emirates is a remote I T and Services opportunity focused on improving the accuracy, reasoning quality, factual reliability, and consistency of next-generation AI systems.

YO IT Consulting is seeking a highly analytical professional who can evaluate model responses, apply complex scoring rubrics, review annotated datasets, and provide precise feedback across business, finance, marketing, healthcare, legal, and research domains.

The role combines AI response evaluation, data annotation, rubric interpretation, quality control, and documentation. The successful contractor will help maintain consistent review standards while contributing practical insights that improve model performance and AI training workflows.

Job Details

• Country: United Arab Emirates
• City: Dubai
• Industry: I T and Services
• Function: Quality Assurance
• Job Type: Contract - Remote - work from home
• Salary: 10000-16000 — Estimated salary range based on similar jobs in the job city; please confirm the final offer with the employer.

Role Context

The AI Trainer Lead will evaluate and classify content used to train and test advanced artificial intelligence models. Assignments may involve comparing multiple responses, scoring reasoning quality, checking factual accuracy, identifying instruction-following failures, annotating datasets, and documenting recurring model weaknesses. The role requires consistent judgment across varied subject areas and large volumes of content. Each evaluation must be supported by clear evidence, accurate rubric application, and actionable feedback that helps project teams refine models, guidelines, and quality standards.

Key Responsibilities

• Evaluate AI-generated responses using defined rubrics, scoring criteria, and project metrics.
• Assess answers for factual accuracy, relevance, coherence, completeness, reasoning quality, and instruction compliance.
• Compare multiple model responses and determine which output best satisfies the task requirements.
• Annotate, categorize, label, and review datasets used for AI model training and evaluation.
• Identify hallucinated facts, unsupported conclusions, contradictions, ambiguity, bias, and logical errors.
• Apply project guidelines consistently across large volumes of content.
• Provide clear written explanations supporting evaluation scores and ranking decisions.
• Deliver specific, actionable feedback that helps improve AI-generated responses.
• Review annotations completed by other contributors for accuracy and consistency.
• Identify recurring quality issues and elevate significant or systematic model failures.
• Collaborate with project teams to interpret complex guidelines and resolve unclear evaluation cases.
• Contribute practical recommendations for refining rubrics, examples, and scoring frameworks.
• Review content across business, finance, marketing, healthcare, legal, research, and general knowledge domains.
• Conduct critical reading of complex material before making evaluation decisions.
• Verify claims and supporting evidence when fact-checking is required.
• Document findings, annotation decisions, edge cases, and quality observations accurately.
• Maintain organized evaluation records, trackers, and project documentation.
• Adapt quickly to new guidelines, task types, subject areas, and evaluation platforms.
• Protect confidential data and follow all project-specific information-handling requirements.
• Work independently while collaborating effectively with distributed remote teams.

Ideal Profile

• Bachelor 's degree from a recognized institution.
• Experience evaluating or scoring substantial volumes of content against detailed criteria.
• Exceptional attention to detail and a strong commitment to accuracy.
• Advanced critical reading, interpretation, and analytical reasoning skills.
• Ability to apply complex rubrics consistently without introducing subjective standards.
• Strong written and verbal English communication skills.
• Ability to explain nuanced quality issues clearly and concisely.
• Experience identifying factual errors, weak reasoning, contradictions, and instruction failures.
• Strong organizational skills for maintaining annotation records and evaluation documentation.
• Ability to work independently in a fully remote contractor environment.
• Comfortable reviewing content across multiple professional and academic domains.
• Experience with AI training, machine learning data annotation, model evaluation, or human-in-the-loop systems is highly valued.
• Background in business, finance, law, marketing, healthcare, research, or a related field is advantageous.
• Familiarity with annotation tools, evaluation platforms, dashboards, or quality trackers is preferred.
• Previous experience supporting quality assurance or reviewing the work of other contributors is beneficial.
• Reliable, responsive, and able to maintain consistent quality across repetitive or high-volume assignments.

Skills Set

• AI response evaluation
• AI model training
• Data annotation
• Content scoring
• Rubric interpretation
• Quality assurance
• Response ranking
• Factual accuracy review
• Critical reading
• Analytical reasoning
• Instruction compliance
• Relevance assessment
• Coherence evaluation
• Error identification
• Hallucination detection
• Bias review
• Content classification
• Dataset labeling
• Quality control
• Written feedback
• Annotation review
• Evaluation documentation
• Guideline interpretation
• Rubric refinement
• Human-in-the-loop systems
• AI evaluation platforms
• Quality trackers
• Cross-domain content review
• Remote collaboration

Why Join Us

This opportunity allows analytical professionals to contribute directly to the improvement of advanced artificial intelligence systems. The work influences how AI models reason, follow instructions, handle factual information, and produce reliable responses across a wide range of professional domains. The remote contract structure offers flexibility while providing exposure to international AI projects, human-in-the-loop evaluation workflows, and emerging model-quality methodologies. It is well suited to candidates who enjoy critical analysis, structured decision-making, and maintaining high standards across complex content-review tasks.

About the Company

YO IT Consulting connects evaluators, trainers, researchers, and domain specialists with remote AI training and quality assurance projects. Operating from Dubai, United Arab Emirates, the company recruits professionals worldwide whose analytical judgment helps improve the accuracy, reasoning, reliability, and practical performance of modern artificial intelligence systems.