Summary
Christopher Flynn is a Principal Engineer with a decade of experience architecting scalable, secure machine learning and data platforms for real-time products across gaming and betting industries. He blends a Mathematics PhD focused on stochastic processes with hands-on engineering—building production ML lifecycles using Python, Airflow, Kubernetes, MLflow, and PostgreSQL, and earlier systems in Go, Spark, and Databricks. As a former director and team lead, he has led cross-functional ML systems teams to productionize realtime model-driven products while maintaining strong software engineering and data governance practices. His background includes research at MIT Lincoln Laboratory and practical analytics work at Zynga and Verizon, giving him rare depth across theory, experiment, and operational scale. He also contributes to open source (github.com/crflynn) and maintains a personal site demonstrating his interest in tooling and reproducible ML infrastructure.
10 years of coding experience
11 years of employment as a software developer
Master of Engineering (M.Eng.) Structural Engineering, Master of Engineering (M.Eng.) Structural Engineering at Lehigh University
Doctor of Philosophy (Ph.D.) Pure and Applied Mathematics, Doctor of Philosophy (Ph.D.) Pure and Applied Mathematics at Stevens Institute of Technology