Nnanyereugo E.

Key Skills

Software

Internal/Proprietary Tooling

Top Subject Matter

Human and Plant Disease detection Reseach

General machine learning model deployment (training/inference support)

Top Data Types

Text

Image

Computer Code Programming

Top Task Types

Data Collection

Classification

Question Answering

Computer Programming/Coding

Freelancer Overview

ML System Developer (ACE-FUELS, Federal University of Technology Owerri). Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Docker. Education includes Bachelor of Technology, Federal University of Technology, Owerri (2023). AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Data Collection and Function Calling.

Labeling Experience

Software & Machine Learning Engineer (BuildX)

Function Calling

Designed and deployed machine learning models for intelligent applications, including neural network systems used in AI-driven automation. Built scalable backend APIs that would support downstream training or inference pipelines. Containerized AI systems and backend services to streamline deployment for model usage. • Implemented ML model and neural network system components for intelligent applications • Built FastAPI backend services to expose ML functionality • Dockerized AI systems and services for efficient deployment • Developed AI-driven automation and decision-support solutions

2025 - Present

ML System Developer (ACE-FUELS, Federal University of Technology Owerri)

TextData Collection

Developed a machine learning data annotation system to support AI research workflows and dataset creation. Worked on improving dataset preparation processes to enable more reliable model training and experimentation. Contributed to intelligent systems aligned with energy-related research initiatives. • Designed the annotation system workflow for preparing research datasets • Improved dataset preparation for subsequent model training • Collaborated with researchers on AI-supported energy initiatives • Supported integration and readiness of data for training experiments

2022 - 2023

Education

Work History