Konstantinos Skoularikis

As a Machine Learning Platform Engineer at Medtronic, I design and maintain production-grade ML infrastructure on AWS, focusing on reliability, scalability, and operational excellence. My work encompasses the full spectrum of MLOps practices, from infrastructure provisioning using Infrastructure as Code to implementing robust CI/CD pipelines that enable data science teams to deploy models with confidence.

My technical expertise includes cloud infrastructure management (AWS, EKS, Karpenter), container orchestration (Kubernetes, Helm), workflow automation (Metaflow, Argo), and comprehensive observability solutions (Prometheus, Grafana). I leverage these technologies to build resilient systems that support the entire machine learning lifecycle, from experimentation to production deployment.

Beyond my professional work, I maintain a homelab environment where I explore infrastructure technologies including Proxmox for virtualization, OPNsense for network security, and K3s for lightweight Kubernetes deployments. This hands-on experience allows me to experiment with emerging technologies and deepen my understanding of systems administration.

With an MSc in Artificial Intelligence from Queen Mary University of London and AWS Solutions Architect certification, I bridge the gap between machine learning research and production systems, ensuring ML workloads operate reliably at scale.

View My Work