Najib Tackie

Contributed to text and image annotation projects supporting AI model training. Used platforms such as Label Studio, CVAT, and Labelbox to upload, review, and validate datasets.

Documented workflows and operational procedures during structured training. Reviewed internal documentation and supported cross-team coordination.

Evaluated AI-generated outputs using quality metrics, relevance scoring, and intent alignment. Tested prompt sensitivity and provided structured feedback to optimize prompt instructions.

Assisted with structured research, tracking, and documentation tasks across distributed teams. Maintained organized records and shared documentation to support operational decision-making.

Reviewed legal documents, case files, and court records with high attention to accuracy. Assisted with transcription and documentation of judicial proceedings, ensuring fidelity and structured formatting.

Performed high-accuracy Akan audio transcription and segmentation for AI model training datasets. Conducted quality assurance checks and followed strict client guidelines to ensure data integrity.

Reviewed AI-generated outputs across NLP and multimodal datasets, ensuring alignment with evaluation rubrics. Performed pairwise comparisons and quality grading, and classified content into structured categories.

Currently pursuing an Associate degree in Computer Science, focusing on foundational computing concepts.

Completed the Artificial Intelligence Career Essentials Virtual Assistant Certification Program, covering AI fundamentals and practical applications.

Pursued a Bachelor of Science in Computer Science, gaining a strong foundation in computing and analytical skills.