Otega O.

Key Skills

Software

CVAT

SuperAnnotate

Appen

iMerit

LabelImg

Micro1

OneForma

Mindrift

Internal/Proprietary Tooling

Top Subject Matter

Multimodal dataset annotation for AI model training (Image focus)

Audio labeling for context/event detection in AI training

Video activity recognition for AI model training

Top Data Types

Image

Geospatial Tiled Imagery

Audio

Top Task Types

Bounding Box

Classification

Action Recognition

Entity (NER) Classification

Segmentation

Object Detection

Question Answering

Text Summarization

RLHF

Evaluation/Rating

Data Collection

Polygon

Freelancer Overview

Data Annotator & AI Quality Analyst. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include CVAT, Label Studio, and SuperAnnotate. Education includes Bachelor of Science in Education, Lagos State University (2021). AI-training focus includes data types such as Image, Audio, and Video and labeling workflows including Bounding Box, Classification, and Action Recognition.

Labeling Experience

Data Annotator & AI Response Analyst (AI Trainer)

Text

I reviewed and analyzed AI-generated text outputs to assess contextual relevance, clarity, coherence, and usability for model improvement. My task involved providing structured, nuanced feedback consistent with evaluation guidelines and the RLHF pipeline. I identified inconsistencies and flagged edge cases to support continuous workflow refinement. • Delivered over 160 data annotations and response evaluations • Assessed both visual and textual AI responses for quality • Followed and refined best practice evaluation guidelines • Supported continuous improvement of AI model development processes.

2025 - Present

Data Annotator & AI Quality Analyst

SuperAnnotateVideoAction Recognition

I participated in high-accuracy activity recognition labeling for AI model pipelines utilizing video data. Labels included defining actions, environments, and contextual sequences in video footage per annotation guidelines. I contributed to maintaining consistent standards for batch-labeling exercises in global remote teams. • Conducted video-based activity recognition and analysis • Implemented detailed action and context labeling • Used platforms such as SuperAnnotate and CVAT • Ensured high volume batch annotation quality and reliability.

2025 - Present

Data Annotator & AI Quality Analyst

Label StudioAudioClassification

I performed labeling and classification of audio files as part of a multimodal dataset annotation pipeline. The work entailed applying structured labels to capture actions, environments, or events within audio clips for training AI models. I continuously reviewed annotation consistency and flagged ambiguous cases for further analysis. • Executed audio data annotation and event labeling for AI applications • Followed detailed guidelines to maximize annotation accuracy • Used annotation platforms including Label Studio • Supported dataset quality control and improvement efforts.

2025 - Present

Data Annotator & AI Quality Analyst

CVATImageBounding Box

I annotated diverse multimodal datasets including images for AI model training in remote settings. My primary focus was on applying precise labels to visual data such as bounding boxes, segmentation masks, and keypoint annotations. I ensured annotation consistency and evaluated annotation quality against established guidelines to maintain high dataset reliability. • Delivered high-accuracy object, action, and contextual relationship labels on images • Used tools such as CVAT, Label Studio, and SuperAnnotate in remote workflows • Maintained consistency and flagged edge cases for QA • Collaborated asynchronously to refine annotation standards and support AI pipelines.

2025 - Present

Education

Work History