malikadeyemo
Ai Research Engineer
AI Research Engineer focused on the evaluation, reliability, and governance of multi-agent LLM systems, currently pursuing an M.Eng in Computer Science at Nagoya Institute of Technology. First-authored peer-reviewed research on contestable AI and supervisor-in-the-loop agent architectures accepted at ITS 2026, with hands-on experience designing LLM-as-Judge evaluation pipelines, multi-criteria scoring rubrics, and human-overseeable agent workflows deployed to real users. Research interests span frontier model evaluation, multi-agent system reliability, contestable and human-in-the-loop AI, and adaptive memory architectures for trustworthy agents.
Experience: 4 years
Yearly salary: $150,000
Hourly rate: $75
Nationality: 🇳🇬 Nigeria
Residency: 🇯🇵 Japan
Experience
AI Guild Lead
Superteam Nigeria 2024 - 2025
Led 30-day intensive bootcamp on building production LLM-powered agents and applications using LangChain ecosystem, with participants successfully landing AI engineering roles and freelance contracts. Mentored 10 teams building AI-powered applications on Solana blockchain, providing technical guidance on agent architecture, prompt engineering, and deployment strategies.
Data Scientist
Outsource Global 2023 - 2024
Engineered high-performance SQL solutions (queries, stored procedures, triggers) for 10M+ row production database, reducing processing time from 30s to 0.5s. Designed and deployed end-to-end analytics infrastructure comprising multiple ETL pipelines and PowerBI dashboards, increasing organizational data utilization by 90% and supporting data-driven strategy. Designed enterprise data warehouse (on-premise) to centralize disparate data sources, improving data governance and reducing query redundancy across 3 departments.
Data Scientist
Hybrid Credit 2023 - 2023
Collaborated with a dynamic team to provide a base framework for financial statement analysis to inform credit scoring for customers with no prior credit history. Created a machine learning pipeline for categorizing each transaction based on information in the transaction description. Built a data pipeline using mono SDK to get financial data from a customer and feed it to a mongoDB database.
Data Science Student Intern
ExploreAI 2023 - 2023
Led cross-functional team of 5 to deploy collaborative filtering movie recommendation system on AWS EC2 with <1s latency, serving 500+ daily predictions via Streamlit interface (Kaggle Challenge). Directed team of 6 in building and deploying regression model for energy load forecasting, achieving 92% prediction accuracy and supporting grid management decisions (Kaggle Challenge). Delivered absenteeism analytics project for 37 employees, identifying 3 key absenteeism drivers and presenting actionable recommendations that informed HR policy changes.
Volunteer Data Science Tutor
NITDA AI Developer Program 2023 - 2023
Trained 142+ students in the application of data science and machine learning to solve business problems.
Machine Learning Intern
National Center for Artificial Intelligence and Robotics 2022 - 2022
Built a ResNet-50 model for diabetic retinopathy detection and ResNet-18 for severity grading, potentially reducing diabetic retinopathy-related blindness by up to 95% through early diagnosis. Developed a chest X-ray classifier on 108,948 frontal-view X-ray images of 32,717 unique patients. Implemented a 3D U-Net model for brain tumor auto-segmentation from 484 3D magnetic resonance imaging scans.
Data Science Intern
Hamoye AI 2022 - 2022
Led a team of 20 interns in the development, evaluation, and deployment of a dementia prediction system. Developed a multi-label images classifier for satellite image chips with various atmospheric conditions. Recognized as the top intern for the stage B data science track out of 400+ interns.
Founder & Lead AI Engineer
FundusAI 2022 - 2025
Developed LLM-powered medical assistant providing personalized health insights with 100% accuracy on patient data interpretation. Built diabetic retinopathy detection system achieving 97% diagnostic accuracy with sub-second inference time.
Skills
ai
aws
ci-cd
docker
prompt
python
english