Agbo Zuma

Hardworking Nigerian medical student pursuing a Bachelor of Medicine, Bachelor of Surgery (MBBS) at the University of Nigeria, Nsukka, with practical experience in AI response evaluation, data annotation, content review, video annotation, software testing, and quality assurance.

Native

Igbo speaker with advanced English proficiency and strong attention to accuracy, linguistic detail, cultural context, and guideline adherence. Experienced in reviewing AI-generated outputs, identifying factual or quality issues, documenting findings clearly, and working independently on structured remote-work platforms.

Freelance AI Data Evaluator & Quality Reviewer at Remote / Global Platforms (2026-06 – Present)

• Evaluate AI-generated prompts, responses, and model outputs using structured quality criteria and project-specific evaluation rubrics.
• Perform data annotation, response ranking, content rating, and dataset quality review for AI training workflows.
• Review textual and visual content for accuracy, relevance, consistency, clarity, naturalness, and compliance with task instructions.
• Identify factual errors, awkward wording, weak reasoning, incomplete labels, and cultural-context issues, then document corrections clearly.
• Apply detailed guidelines consistently across repetitive or ambiguous tasks while maintaining attention to detail and quality standards.
• Work independently in remote environments, manage task deadlines, and maintain structured documentation for review decisions.

Software Quality Tester at Software Quality Testing

• Execute structured mobile application test cases to identify functional issues, crashes, and abnormal application behavior.
• Test applications under slow-network, offline, and airplane-mode conditions to assess stability and content-loading performance.
• Document bugs and test findings clearly, including steps to reproduce issues and observed results.
• Compare expected and actual behavior carefully and report repeatable defects using clear, structured notes.

AI Annotation & Captioning Training at Annotasks / Encord (2026 – 2026)

• Completed structured video-annotation training involving temporal segmentation, action captioning, and detailed segment-level descriptions.
• Applied annotation rules covering visible actions, hand-object interactions, timing accuracy, label consistency, and quality review.
• Reviewed AI-generated pre-captions and corrected inaccurate or incomplete labels based on observable video evidence.
• Worked with task-specific instructions requiring precise observation, consistency, and evidence-based annotation decisions.

Bachelor of Medicine, Bachelor of Surgery in MBBS – University of Nigeria, Nsukka (UNN) - College of Medicine, Enugu Campus