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Abdul Qadir Shonibare

Abdul Qadir Shonibare

ML Developer (Data Collection & Preparation for AI Training)

Nigeria flagLagos, Nigeria
$16.00/hrEntry LevelAws SagemakerRoboflow

Key Skills

Software

AWS SageMakerAWS SageMaker
RoboflowRoboflow

Top Subject Matter

Nlp Domain Expertise
speech/text processing
language data

Top Data Types

TextText
ImageImage
AudioAudio

Top Task Types

Data CollectionData Collection
ClassificationClassification
Emotion RecognitionEmotion Recognition

Freelancer Overview

ML Developer (Data Collection & Preparation for AI Training). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Python, Pandas, and NumPy. Education includes Bachelor of Science, University of Ilorin (2023). AI-training focus includes data types such as Text, Image, and Audio and labeling workflows including Data Collection, Classification, and Emotion Recognition.

Entry LevelEnglish

Labeling Experience

ML Developer (Data Collection & Preparation for AI Training)

TextData Collection
As an ML Developer at RendoAI, I collected and curated multilingual datasets in various Nigerian languages to increase the quality and diversity of training data. I performed data cleaning, preprocessing, and normalization to ensure high-quality input for downstream NLP and speech/text processing tasks. My work helped improve model generalization and readiness for deployment. • Built and optimized data pipelines for efficient transformation and ingestion • Conducted exploratory data analysis to identify inconsistencies and patterns • Implemented validation techniques to reduce data noise and improve integrity • Documented workflows for reproducibility and scalability.

As an ML Developer at RendoAI, I collected and curated multilingual datasets in various Nigerian languages to increase the quality and diversity of training data. I performed data cleaning, preprocessing, and normalization to ensure high-quality input for downstream NLP and speech/text processing tasks. My work helped improve model generalization and readiness for deployment. • Built and optimized data pipelines for efficient transformation and ingestion • Conducted exploratory data analysis to identify inconsistencies and patterns • Implemented validation techniques to reduce data noise and improve integrity • Documented workflows for reproducibility and scalability.

2023 - Present

ML Associate (Voice Emotion Recognition Data Labeler)

AudioEmotion Recognition
As an ML Associate at PROGNOZ.AI, I contributed to a team project on voice emotion recognition by participating in data collection, annotation, and preprocessing of audio recordings. I labeled emotion categories within voice samples to build reliable datasets for supervised training. This labeling supported the development and validation of the emotion recognition model. • Collaborated on data integrity and consistency across sources • Evaluated data quality for training and validation • Used Python tools for preprocessing and formatting • Participated in cross-functional review and enhancement of labeled data.

As an ML Associate at PROGNOZ.AI, I contributed to a team project on voice emotion recognition by participating in data collection, annotation, and preprocessing of audio recordings. I labeled emotion categories within voice samples to build reliable datasets for supervised training. This labeling supported the development and validation of the emotion recognition model. • Collaborated on data integrity and consistency across sources • Evaluated data quality for training and validation • Used Python tools for preprocessing and formatting • Participated in cross-functional review and enhancement of labeled data.

2022 - 2023

AI Training/Annotation: Brain Tumor Image Classification Researcher

ImageClassification
I led the collection and annotation of a brain MRI image dataset for tumor detection research using CNNs. Tasks included image ingestion, resizing, normalization, noise removal, balanced class representation, and dataset splitting for supervised training. I ensured high-quality dataset preparation for deep learning model development. • Performed labeling for tumor/non-tumor classes on MRI images • Handled dataset balancing to enhance model accuracy • Implemented preprocessing for noise reduction and normalization • Monitored data quality during model training and evaluation.

I led the collection and annotation of a brain MRI image dataset for tumor detection research using CNNs. Tasks included image ingestion, resizing, normalization, noise removal, balanced class representation, and dataset splitting for supervised training. I ensured high-quality dataset preparation for deep learning model development. • Performed labeling for tumor/non-tumor classes on MRI images • Handled dataset balancing to enhance model accuracy • Implemented preprocessing for noise reduction and normalization • Monitored data quality during model training and evaluation.

2022 - 2023

Education

U

University of Ilorin

Bachelor of Science, Information and Communication Science

Bachelor of Science
2018 - 2023

Work History

S

Steghub

Data Analytics Intern

Lagos
2025 - Present
R

RendoAI

ML Developer

Lagos
2023 - Present