AI & ML
Building intelligent systems, training models, and designing pipelines from LLMs to automation frameworks that solve real problems at scale.
Artificial Intelligence is not just about models; it's about systems. I specialize in architecting end-to-end ML pipelines, fine-tuning Large Language Models (LLMs) for specific domains, and deploying scalable inference engines. My approach combines academic rigor with practical engineering to turn 'magic' into reliable software.
Fine-tuning, RAG architectures, and prompt engineering for enterprise applications.
Computer vision and NLP models built on PyTorch and TensorFlow.
Automated training pipelines, model monitoring, and scalable deployment on cloud infrastructure.
Most AI projects fail not because of model quality but because of poor problem definition, inadequate data pipelines, or misaligned expectations. My consulting approach addresses the full stack: from identifying which business problems are genuinely solvable with ML, through data preparation and model development, to production deployment and monitoring.
I work with organisations at every stage, from building their first AI proof of concept to scaling existing ML systems for enterprise reliability. Whether you need a custom LLM pipeline, a computer vision solution, or a generative AI product integrated into your workflow, the engagement starts with clarity about the problem and ends with a system you can trust.
Assessing your data assets, team capabilities, and business goals to define an executable AI roadmap.
Custom ML models for classification, prediction, recommendation, and generation: built on your data.
Containerised, monitored, and scalable AI systems deployed on AWS, GCP, or Azure cloud infrastructure.