Ugochukwu F.

Key Skills

Software

SuperAnnotate

Top Subject Matter

NLP training data

written instruction and evaluation content

Computer vision video annotation for AI model training

Top Data Types

Text

Video

Audio

Image

Document

Top Task Types

Text Generation

Tracking

Transcription

Entity (NER) Classification

Freelancer Overview

Content Writer & Data Annotator (SuperAnnotate, remote). Core strengths include SuperAnnotate, Internal, and Proprietary Tooling. Education includes Bachelor of Science, Imo State University (2022). AI-training focus includes data types such as Text, Video, and Audio and labeling workflows including Text Generation, Tracking, and Transcription.

Labeling Experience

Content Writer & Data Annotator (SuperAnnotate, remote)

SuperAnnotateTextText Generation

Created written training data to support natural language model development and ensured outputs aligned with project guidelines. Annotated and curated text datasets to improve grammar, clarity, and accuracy for downstream AI training. Collaborated with annotation teams to refine workflows, maintain consistency, and meet strict deadlines. • Produced creative and structured training content • Reviewed dataset quality for accuracy and guideline compliance • Supported multilingual/grammar-focused dataset refinement • Coordinated with QA and team members to standardize labeling

2025 - 2025

Data Annotator (Hugotech AI)

TextEntity (NER) Classification

Tagged and annotated training data for NLP and visual recognition projects using internal annotation protocols. Participated in feedback loops to refine annotation guidelines and improve consistency across annotators. Contributed to high-quality labeled datasets intended for AI model training and evaluation. • Performed NLP data tagging and annotation • Supported visual recognition data labeling • Provided feedback to improve labeling protocols • Ensured labeled outputs met internal quality expectations

2024 - 2024

Data Annotator – Video & Image Projects (Moonvalley, remote)

VideoTracking

Delivered structured annotations for computer vision tasks across diverse image and video datasets. Labeled people, objects, and scene changes in complex video sequences while maintaining batch-level consistency. Followed internal tools and clear project guidelines to ensure reliable coverage across frames and sequences. • Annotated entities and scene events in video • Maintained labeling consistency across dataset batches • Applied project instructions for accurate tagging • Produced completed annotation deliverables under deadlines

2024 - 2024

Data Annotation Specialist – AI Model Training (e2f Inc., remote)

AudioTranscription

Participated in multilingual data labeling including speech-to-text alignment, image tagging, and metadata verification for training data preparation. Coordinated with QA reviewers to meet required data accuracy thresholds and improve dataset quality. Ensured labeled outputs matched annotation protocols for reliable model training inputs. • Performed speech-to-text alignment tasks • Verified and corrected metadata for training records • Applied image tagging for multimodal datasets • Worked with QA to reach accuracy and quality targets

2023 - 2024

Education

Work History