Infrastructure & Systems Engineer with 3 years of production experience (Capgemini), AWS certified, now building toward MLOps — bringing machine learning models to production reliably, at scale.
My edge is a solid infrastructure foundation: MLOps is DevOps applied to ML, so I'm building the full stack in public — one project, one milestone at a time.
- 🛠️ DevOps foundation (now): Linux, Docker, CI/CD (GitHub Actions), Infrastructure as Code (Terraform), Kubernetes.
- 🤖 MLOps core (next): experiment tracking & model registry (MLflow), model serving, CI/CD for ML, drift monitoring.
- 🧠 LLMOps (the goal): RAG pipelines, vector databases, and deploying & operating LLMs in production.
- AWS Certified CloudOps Engineer – Associate
- In progress / next: RHCSA · Terraform Associate · CKA · AWS ML Engineer – Associate
- 📍 Project 1: End-to-end MLOps pipeline — (coming soon as I build it!)
- 📝 Blog / Notes: documenting my path from infrastructure to MLOps, step by step.