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Kimani Joel

Kimani Joel

Transcription Specialist/ Ai Trainer

Talent
NairobiMember since April 21, 2026
Visual AnalysisCompositionLightingCamera MovementFrame-by-frame Motion RealismMedia Production QASpatial and Temporal ConsistencyCVATLabelboxPrompt EngineeringText-to-Image GenerationText-to-Video GenerationPythonPython AutomationPython ValidationJupyter NotebooksCSV Metadata ReviewJSON Metadata ReviewMotion TrackingBounding BoxesFrame-by-frame ConsistencySpatial LogicAnalytical LogicMathematical LogicInstruction Adherence EvaluationFactuality ChecksStatistical Anomaly DetectionData AnnotationGround Truth Labeling
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Visual AnalysisCompositionLightingCamera MovementFrame-by-frame Motion Realism

About

Creative-focused Data Annotation professional with a Bachelor's in Mathematics and an expert eye for visual storytelling. Experienced in evaluating high-fidelity AI-generated imagery and video content for production-level standards. Skilled in auditing motion realism, lighting, and composition within complex rating frameworks to drive advanced LLM and multimodal model development.

Experience

AI Trainer & Arts Evaluator at Mindrift (2024-01 – Present)

Ranked and compared AI-generated multimodal responses, prioritizing visual relevance, stylistic instruction adherence, and aesthetic quality. Conducted deep-dive factuality and logical consistency checks on prompts involving complex visual scene descriptions.

  • Ranked and compared AI-generated multimodal responses, prioritizing visual relevance, stylistic instruction adherence, and aesthetic quality
  • Conducted deep-dive factuality and logical consistency checks on prompts involving complex visual scene descriptions
  • Integrated feedback from LLM performance metrics into the creation of high-quality training datasets
  • Utilized Python scripts to validate large-scale media metadata and ensure structural integrity before submission

Image & Video Quality Specialist at OpenScale AI (2025-01 – Present)

Audited large-scale video datasets for production quality, focusing on motion realism and object interaction. Performed meticulous frame-by-frame video reviews using CVAT and Labelbox to ensure temporal consistency and lighting accuracy.

  • Audited large-scale video datasets for production quality, focusing on motion realism and object interaction
  • Performed meticulous frame-by-frame video reviews using CVAT and Labelbox to ensure temporal consistency and lighting accuracy
  • Created high-accuracy 'Ground Truth' labels for complex action sequences, bridging the gap between raw footage and AI-ready data
  • Collaborated with remote review teams to resolve subjective guideline clarifications regarding aesthetic 'production standards'

Education

Bachelor of Science in Mathematics – University of Nairobi

Certification in AI for Software Engineering – ALX Africa

Skills

Transcription Specialist/ Ai Trainer

Reviews