Professional Overview
Results-driven MLOps Engineer and Data Scientist with experience in designing, deploying, and optimizing end-to-end machine learning pipelines and AI-driven solutions using Python. Hands-on expertise in CI/CD for ML, workflow automation, experiment tracking, model monitoring, and performance improving in production environments.
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.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
data science & analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
