Professional Overview
AI/ML Engineer and Data Engineer with experience building end-to-end machine learning pipelines, NLP and LLM applications, and cloud-native AI solutions. Skilled in Python, AWS, Docker, Kubernetes, SQL, PyTorch, and MLOps practices. Passionate about designing scalable, production-ready AI systems that solve complex business challenges and deliver m
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.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.