I will deliver senior-level machine learning and data science solutions with full deployment — per hour

Senior-level ML projects are complex and every one is different. I need to understand your data landscape, business objectives, technical constraints, and expected outcomes before I can scope the work properly. This conversation protects both of us — you get an accurate estimate and clear deliverables, and I can confirm I'm the right fit for what you need before any money changes hands.

Each package represents a block of hours at my senior hourly rate. Choose the package closest to your project size and use the quantity selector to scale up if needed. For example, 3x of the Standard gives you 15 hours. We'll agree on exact scope and milestones before you place your order.

I'll let you know well before we reach the limit. We'll discuss whether to extend the scope or reprioritise deliverables within the agreed hours. You're never billed for time we haven't explicitly agreed on.

Both are hands-on engineering services — I write code, build models, and deploy systems in both. The difference is the complexity and depth of work. This senior-tier service is for projects that involve advanced architectures, multi-component system design, full CI/CD pipeline setup, and production-grade deployment with comprehensive documentation. My standard ML Engineering Zinn is better suited to focused, well-defined tasks like single model training, data preprocessing, or straightforward deployments. If you're unsure which fits your project, message me and I'll recommend the right one.

Yes. You'll need to supply the dataset or data source. During our scoping conversation I'll advise on data format requirements, volume considerations, quality expectations, and any preprocessing that should be done before we begin.

My primary deployment platforms are Google Cloud Platform and Hugging Face. I set up full CI/CD pipelines using Docker, GitHub Actions, and MLflow so your deployed system is maintainable, scalable, and easy to update after handover.

Yes. All source code, trained models, pipeline configurations, and documentation are yours. I deliver everything you need to maintain, retrain, and extend the system independently after the project is complete.

Yes. I regularly step into existing projects that have stalled, hit technical walls, or need senior-level engineering to reach production. Share what you have during our scoping conversation — code, notebooks, documentation, whatever exists — and I'll assess the current state and build from where things stand rather than starting from scratch.

It typically includes automated model retraining triggers, containerised deployment using Docker, GitHub Actions for continuous integration, MLflow for experiment tracking and model versioning, and deployment scripts for GCP or Hugging Face. The exact setup depends on your project requirements — we'll define this during scoping.

Yes, every package includes documentation proportional to the work delivered. The Premium tier includes full technical documentation covering system architecture, data pipeline specifications, model performance reports, deployment instructions, and maintenance guidance — everything a future developer or your internal team would need to understand and manage the system.

No. Every package is hands-on engineering. The Basic single hour is real development time — I'll be writing code, building pipeline components, evaluating models, debugging issues, or solving technical problems. It's not a chat about what could be done — it's an hour of actual senior-level work getting done. It's ideal for smaller focused tasks, urgent fixes, or making meaningful progress on a specific part of a larger project.