Summary
Matt Camack is an experienced platform and machine learning engineer with nine years of hands-on experience designing and productionizing cloud-native systems and ML workflows. He has led developer platform and automation efforts at Secureworks and Lockheed Martin, building internal platforms with Backstage, Argo, Kubeflow, Helm, and GitLab CI to convert weeks-long manual processes into fully automated pipelines. At PlayStation he bridged data science and engineering to productionize time-series and real-time anomaly detection systems using TensorFlow, SageMaker, and EKS, and he’s comfortable across DevOps, infrastructure-as-code, and monitoring stacks. A former systems and electronics engineer with advanced degrees in electrical and space systems engineering, he brings rigorous systems thinking to software architecture and CI/CD design. Now running his own studio in San Diego, he combines entrepreneurial drive with deep cross-domain expertise in ML, Kubernetes, and cloud automation. An under-the-radar strength is his track record of translating experimental research notebooks into reusable, production-ready frameworks that scale across teams.
9 years of coding experience
15 years of employment as a software developer
California Polytechnic State University, San Luis Obispo
Master of Engineering (M.Eng.) Space Systems Engineering, Master of Engineering (M.Eng.) Space Systems Engineering at Stevens Institute of Technology