ML Engineer, AI Engineer, Full-Stack Engineer, AWS & Azure Cloud Engineer.
I build machine learning systems, AI applications, cloud platforms, and full-stack products that are designed to run in production, not just in notebooks or slide decks.
End-to-end engineering across models, product, and operations.
This is the layer where most search pages get vague. Mine should not. I work across the parts that actually determine whether a system becomes useful: model quality, product shape, cloud infrastructure, deployment, and operational reliability.
Machine Learning Engineering
Model training, evaluation, forecasting, anomaly detection, ranking, experimentation, monitoring, and deployment pipelines for production systems.
AI Engineering
RAG systems, Azure OpenAI workflows, prompt orchestration, evaluation loops, and practical AI features that fit inside real business operations.
Full-Stack and Cloud Delivery
Backend services, APIs, public-facing interfaces, deployment workflows, payments, messaging, and the operational glue that makes software stay live.
AWS, Azure, and the operational layer around them.
I am not only interested in models. I work on the systems that surround them: compute environments, APIs, storage, pipelines, observability, and deployment processes.
Azure Delivery
AWS Delivery
Operations
Product Engineering
Evidence from shipped work.
Search intent is one thing. Proof is another. These are the environments where I have actually delivered ML, AI, cloud, and operational work.
— Present
- Production checkout conversion modelling across 9 markets
- AI-powered reporting workflows using Azure OpenAI
- Cloud and data platform delivery spanning Azure ML, AKS, Synapse, and Snowflake
— 2025
- Forecasting and anomaly detection for water infrastructure
- Operational data science for critical infrastructure planning
- Energy forecasting and grid-oriented operational analytics
- AWS-based data and optimisation work in renewables
Common hiring and search questions.
Can you build both ML systems and software products?
Yes. I work across modelling, APIs, infrastructure, deployment, and user-facing product delivery, which is why my portfolio includes both ML systems and live web platforms.
Do you work across AWS and Azure?
Yes. My work includes Azure ML, Azure OpenAI, AKS, Synapse, and Azure DevOps as well as AWS Lambda, DynamoDB, S3, CloudFront, SES, and Route 53.
Do you handle operations and deployment too?
Yes. I care about what happens after the model or product is built: CI/CD, cloud setup, release workflows, reliability, and the operational edges that determine whether a system keeps working.