Professional Overview
I am a Machine Learning Engineer and Software Developer with a strong foundation in Python, TensorFlow, and scalable backend systems. I specialize in building end-to-end ML solutions from data preprocessing and feature engineering to model deployment and monitoring in production environments. My experience includes developing predictive models, optimizing performance through cross-validation and hyperparameter tuning, and deploying models via REST APIs using Docker and cloud platforms.With a background in Information Technology and hands-on experience in full-stack development, I bridge the gap between machine learning research and real-world business applications. I focus on delivering clean, maintainable code and measurable results whether improving model accuracy, reducing inference latency, or building automated ML pipelines.I am open to remote contract opportunities in machine learning, data science, and AI engineering where I can help teams build intelligent, scalable solutions.
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
