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Nwankwo N.

Nwankwo N.

AI Data Annotator | Architecture & Technical Drawing

Nigeria flagIkeja, Nigeria

Key Skills

Software

Other

Top Subject Matter

Architectural technical drawings and document annotation for AI dataset preparation
AI/ML training fundamentals and dataset labeling context
Image and visual data annotation for computer vision models

Top Data Types

DocumentDocument
ImageImage

Top Task Types

Entity (NER) ClassificationEntity (NER) Classification

Freelancer Overview

I am a detail-oriented Architecture graduate with a 4.0 GPA from Nnamdi Azikiwe University, Nigeria. My years of technical drawing and design work have sharpened my visual accuracy, pattern recognition, and ability to follow strict guidelines — skills that transfer directly to data labeling and AI training tasks. I am proficient in AutoCAD, Revit, ArchiCAD, and Microsoft Office, and I am actively learning programming to deepen my understanding of AI systems. I am highly consistent, self-motivated, and able to handle high-volume annotation tasks with accuracy and focus.

Labeling Experience

Independent Technology & Programming Learner (AI training context)

Other

Since 2023, the candidate has been self-directedly exploring programming fundamentals and building understanding of how AI models are trained. This learning provides context for how labeled datasets drive model behavior and evaluation. While not an explicit paid labeling role, the stated focus aligns with preparation for AI training and data-labeling requirements. • Developing familiarity with AI model training workflows and the role of labeled data • Practicing programming fundamentals to support future AI training tasks • Applying self-directed learning to improve understanding of annotation needs • Building domain knowledge relevant to ML dataset preparation

2023 - Present

Architectural Design & Technical Drawing (Annotation-adjacent tagging/classification and QA)

OtherDocumentDocumentEntity (NER) ClassificationEntity (NER) Classification

During 2020–2024, the candidate produced, reviewed, and interpreted large volumes of technical architectural drawings using standardized guidelines and error-detection practices. The work included precise tagging and classification of drawing elements, mirroring key requirements of annotation pipelines that rely on consistent labeling. Their QA-style peer review mirrors label validation and quality control used in dataset production. • Interpreted complex design standards and applied them consistently across many documents • Annotated and classified drawing elements with high accuracy and attention to detail • Conducted review and error checking to ensure guideline adherence • Maintained output consistency across large datasets of technical drawings

2020 - 2024

Education

N

Nnamdi Azikiwe University

Bachelor of Science, Architecture

Bachelor of Science
2021 - 2025

Work History

K

Keb Enterprises

Graphic Designer

Ojodu Berger
2020 - 2023