Kayode M.

Key Skills

Software

Scale AI

Labelbox

Remotasks

CVAT

Top Subject Matter

NLP and Machine Learning

Image Classification and Object Detection

Speech Recognition and Audio Processing

Top Data Types

Computer Code Programming

Text

Image

Audio

Video

Top Task Types

Bounding Box

Classification

RLHF

Transcription

Evaluation/Rating

Prompt + Response Writing (SFT)

Entity (NER) Classification

Segmentation

Freelancer Overview

AI Data Annotator (Text/NLP). Core strengths include Scale AI, Labelbox, and Remotasks. AI-training focus includes data types such as Text, Image, and Audio and labeling workflows including Entity (NER) Classification, Bounding Box, and Transcription.

Labeling Experience

Data annotation

DocumentBounding Box

This project involved data annotation and labelling tasks aimed at training and improving Ai/machine learnining models.The scope covered annotating large datasets of text,images, and/or audio samples to enable accurate model recognition and response. Specific tasks peerformed included text classification,sentiment labelling, and quality review of labeled datasets. each task required careful reading and understanding of annotation guidelines to ensure consistency accross all enteries. The project handled a datasets of over tasks X tasks or items completed within a defined timeframe, making it a medium to large scale annotation project.. All work was completed with attention to detail,accuracy, and consistency, contributing directly to the development of well trained AI system

2025 - Present

AI Data Annotator (Video)

CVATVideoSegmentation

As part of my video annotation responsibilities, I conducted segmentation, object detection, and action recognition tasks for machine learning datasets. I applied project-specific policies to ensure accurate video labeling and adhered to data integrity standards during annotation and review. My efforts contributed directly to the development and refinement of advanced computer vision models. • Used tools such as CVAT, Scale AI, and Labelbox • Followed evolving project guidelines and annotation requirements • Reviewed peer work to identify and correct inconsistencies • Maintained accurate, high-volume throughput on video labeling assignments.

Present

AI Data Annotator (Audio)

RemotasksAudioTranscription

I labeled and transcribed audio datasets for use in machine learning projects, ensuring precise capture of spoken content and speech characteristics. Transcription and audio labeling efforts followed project-specific annotation guidelines and quality assurance protocols. I also contributed to the peer review process for enhanced dataset reliability and integrity. • Employed platforms like Remotasks and Appen for audio annotation • Ensured transcriptions met high accuracy and completeness standards • Identified and flagged ambiguous or unclear audio samples • Improved model performance using consistently high-quality data.

Present

AI Data Annotator (Image/Computer Vision)

LabelboxImageBounding Box

In my role as Machine Learning Data Specialist, I performed image data labeling using bounding boxes, semantic segmentation, and keypoints annotation. This supported object detection and image classification machine learning tasks across multiple client projects. I ensured consistent accuracy by following detailed labeling guidelines and schema updates. • Utilized tools including Scale AI, Labelbox, CVAT, and Remotasks • Followed updated annotation schemas and project instructions • Regularly participated in peer quality reviews and feedback sessions • Maintained high throughput of annotated images under tight deadlines.

Present

AI Data Annotator (Text/NLP)

Scale AITextEntity (NER) Classification

As an AI Data Annotator, I labeled and validated large-scale datasets specifically for natural language processing and machine learning tasks. My work included text classification, named entity recognition, sentiment labeling, and RLHF ranking using industry annotation standards. I collaborated closely with project leads and QA teams to ensure all annotations met stringent client requirements and maintained high accuracy levels. • Maintained annotation accuracy rates above 95% consistently • Reviewed peer work for quality assurance and guideline compliance • Used platforms such as Scale AI, Appen, Remotasks, and Labelbox • Contributed to AI model improvement through high-quality data.

Present

Education

Work History