Victor Nyabuto
Machine Learning Engineer
I design and build intelligent systems that combine machine learning, scalable backend engineering, and modern web technologies to solve real-world problems through data-driven decision systems.
Victor Nyabuto
ML Engineer • Full-Stack Developer
Primary Focus
ML + Product Engineering
Working Style
Clean, scalable, practical
Current Identity
Machine Learning Engineer
Focused on building systems that learn from data, support decision-making, and operate reliably in production environments.
ML
Models
UX
Interface
API
Systems
About Me
I am a Machine Learning Engineer and Full-Stack Developer focused on designing and building intelligent, data-driven systems that bridge software engineering with applied artificial intelligence. My work sits at the intersection of scalable backend systems, modern web technologies, and machine learning pipelines.
I enjoy working across the full lifecycle of intelligent systems — from data processing and feature engineering to model development and production deployment. My approach emphasizes clean architecture, performance, and practical applicability in real-world environments where reliability and interpretability matter.
Beyond model development, I am deeply interested in system design for AI applications, including how data flows through applications, how models are integrated into user-facing products, and how engineering decisions impact scalability and maintainability.
I continuously explore advancements in machine learning, software engineering practices, and distributed systems, with a strong focus on building solutions that are both technically sound and practically useful.
Skills
frontend
React, Next.js, Tailwind
backend
Django, Flask
ml
Scikit-learn, TensorFlow, LSTM
databases
MySQL, MongoDB
Projects
Selected engineering systems and AI applications
Machine Learning
BitPredictor
End-to-end machine learning system for Bitcoin price forecasting using LSTM networks, time-series feature engineering, and backtesting simulation for strategy validation.
Machine Learning / Systems
Log Anomaly Detector
Machine learning system designed to detect anomalies in system logs using unsupervised learning techniques for monitoring and operational intelligence.
Data Science / Web App
GameXPredic
Predictive analytics platform for forecasting global video game sales using structured market and review data with regression-based machine learning models.
Machine Learning
Diabetes Predictor
Medical classification model predicting diabetes risk using structured patient health indicators and supervised learning techniques.
Financial AI / Data Science
Macroeconomic Event Analyzer
AI-driven analytical system that evaluates how macroeconomic indicators such as CPI, unemployment rate, and interest rates influence financial market sectors.
NLP / Data Intelligence
Reddit Sentiment Tracker
Natural language processing system that collects, analyzes, and visualizes sentiment trends from Reddit discussions in real time.
Full-Stack / Systems
University Management System
Basic academic management system for handling student records, courses, and administrative operations in a structured database system.
Experience
AI Hackathon – Career Recommendation System
Built an end-to-end ML-based career recommendation system during a competitive university AI hackathon. Designed data preprocessing pipelines, model training workflow, and deployed a working prototype under time constraints.
Log Anomaly Detection System (Production-Ready)
Developed a full-stack Flask + ML system for anomaly detection in system logs using Isolation Forest and LSTM-based sequence modeling. Implemented user authentication, log upload pipelines, and interactive anomaly visualization. Deployed and maintained on GitHub.
BitPredictor – Deep Learning Market Forecasting
Integrated LSTM-based forecasting into a Streamlit dashboard for financial time-series prediction. Built modular pipeline for data ingestion, training, evaluation metrics, and interactive predictions.
Macroeconomic Event Impact Analyzer
Designed a Streamlit-based analytics platform combining FRED, Yahoo Finance, and macroeconomic indicators. Applied XGBoost and Prophet models to analyze and forecast sector reactions to economic events.
Warehouse Robot Navigation (Reinforcement Learning)
Built a reinforcement learning environment for path optimization in warehouse navigation. Designed agent training loop, reward system, and simulation visualization with modular Python architecture.
AidConnect – Disaster Response Coordination System
Architected a crowdsourced disaster reporting platform using Django + React + MongoDB. Designed geolocation-based reporting system, modular backend APIs, and planned SMS notification integration via Twilio.
NeuroTwin – Digital Behavioral AI System
Developed a Streamlit-based behavioral logging and predictive digital twin system using machine learning models for pattern recognition and user behavior simulation.
GameXPredic
Built a Django-based video game sales prediction system using machine learning models. Implemented data pipeline, model training workflow, and web-based prediction interface as a full production-style academic capstone.
Contact
Let us build something impactful together.
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