Emmanuel Chukwuebuka Anichi

Key Skills

Software

Telus

Lionbridge

Toloka

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Document

Image

Text

Video

Top Label Types

Action Recognition

Bounding Box

Classification

Data Collection

Emotion Recognition

Evaluation Rating

Object Detection

Freelancer Overview

I am a detail-oriented AI Data Labeler and Annotator with hands-on experience working on image, text, and audio annotation projects for leading platforms such as Telus Digital, Lionbridge, and Toloka. My background includes labeling and validating datasets for computer vision and NLP tasks, evaluating AI-generated outputs, and maintaining high accuracy and productivity in remote environments. I am skilled in using web-based annotation tools like Aurora Studio, as well as Google Workspace and Microsoft Office. I excel at following complex guidelines, identifying edge cases, and ensuring data quality through careful review and consistent decision-making. My strong analytical skills, fast learning ability, and commitment to meeting deadlines make me a reliable contributor to any AI training data project. I have worked in several projects such as Project Sonic on Telus Digital which used the Parimango and Multimango as their data annotation tool. I have also worked the Aurora studio app which is the Ai data training tool used by Lionbridge.

Labeling Experience

AI Data Annotator / Data Labeler — Lionbridge

LionbridgeTextClassification

Contributed to AI training projects through structured data labeling and categorization tasks. Evaluated search, text, and visual data according to strict project-specific rules and instructions. Supported model improvement efforts with careful judgment and detailed feedback.• Performed quality assurance and met defined quality thresholds. • Categorized and tagged datasets used for various AI use cases. • Maintained compliance with extensive labeling guidelines. • Collaborated remotely to deliver high-volume task completions.

Contributed to AI training projects through structured data labeling and categorization tasks. Evaluated search, text, and visual data according to strict project-specific rules and instructions. Supported model improvement efforts with careful judgment and detailed feedback.• Performed quality assurance and met defined quality thresholds. • Categorized and tagged datasets used for various AI use cases. • Maintained compliance with extensive labeling guidelines. • Collaborated remotely to deliver high-volume task completions.

2025

AI Data Annotator — Telus Digital

TelusImageEvaluation Rating

Performed high-accuracy labeling and validation of text, image, and audio datasets for AI model training. Applied detailed annotation guidelines across large task volumes, ensuring consistency and precision. Reviewed and rated AI-generated outputs for relevance, safety, and cultural appropriateness.• Conducted quality checks and flagged ambiguous or edge-case data. • Maintained productivity targets and accuracy standards in remote workflows. • Delivered consistent, high-quality results using web-based platforms. • Demonstrated adaptability with multiple data types and annotation tasks.

Performed high-accuracy labeling and validation of text, image, and audio datasets for AI model training. Applied detailed annotation guidelines across large task volumes, ensuring consistency and precision. Reviewed and rated AI-generated outputs for relevance, safety, and cultural appropriateness.• Conducted quality checks and flagged ambiguous or edge-case data. • Maintained productivity targets and accuracy standards in remote workflows. • Delivered consistent, high-quality results using web-based platforms. • Demonstrated adaptability with multiple data types and annotation tasks.

2025

AI Training & Annotation Contributor — Toloka

TolokaImageClassification

Completed diverse micro-tasks including classification, tagging, verification, and relevance judgment for NLP and computer vision. Labeled datasets intended for training advanced AI models, ensuring strong consistency across all assignments. Maintained high acceptance rates by rigorously adhering to annotation guidelines and project objectives.• Performed fine-grained data labeling and validation on Toloka’s online platform. • Managed repetitive and high-volume annotation tasks efficiently. • Participated in feedback cycles to refine labeling processes. • Delivered time-sensitive outputs with accuracy and reliability.

Completed diverse micro-tasks including classification, tagging, verification, and relevance judgment for NLP and computer vision. Labeled datasets intended for training advanced AI models, ensuring strong consistency across all assignments. Maintained high acceptance rates by rigorously adhering to annotation guidelines and project objectives.• Performed fine-grained data labeling and validation on Toloka’s online platform. • Managed repetitive and high-volume annotation tasks efficiently. • Participated in feedback cycles to refine labeling processes. • Delivered time-sensitive outputs with accuracy and reliability.

2024

Education

Work History