Summary
Johannes Damp is a Senior Software Engineer and data scientist with a PhD in experimental particle physics and nine years of experience turning large, noisy datasets into actionable insight. He moved from leading ML-driven particle reconstruction and trigger/data-acquisition software at CERN and Mainz to delivering cloud-native AI and MLOps solutions for finance and enterprise, notably provisioning private AI infrastructure and self-service GPU environments. Johannes blends deep statistical rigor (maximum-likelihood and Bayesian methods) with production-grade engineering—CI/CD, Terraform, ArgoCD, and containerized deployments—to shorten release cycles and scale secure ML workflows. He has hands-on experience across the stack including C++, Python, PyTorch, SQL and firmware-level systems that handled petabytes/year of collider data. A pragmatic collaborator and supervisor of early-career researchers, he consistently bridges research and operational delivery, translating physics-grade experimental practices into robust engineering processes. Less obvious: his background in real-time trigger systems gives him rare expertise in latency-sensitive, high-throughput pipelines that benefit both scientific and commercial ML platforms.
9 years of coding experience
4 years of employment as a software developer
Doktor (Ph.D.) Physik, Doktor (Ph.D.) Physik at Johannes Gutenberg University Mainz