Summary
Mason Malone is a Machine Learning Operations Software Engineer with nine years of experience building scalable, production-grade systems across AWS and enterprise environments. He helped launch Amazon’s Amp, designing real-time ML inference pipelines, streaming feature ingestion, and personalized recommendation APIs using a broad AWS stack (SageMaker, Lambda, Fargate, Kinesis, MemoryDB, S3). At Boeing he continues to apply MLOps rigor to operationalize models and data workflows, combining software engineering discipline with DevOps and compliance automation. Known for implementing end-to-end testing, automated rollbacks, and on-demand data deletion processes, he balances fast iteration with legal and reliability constraints. Based in Seattle, he pairs a BS in Computer Science with hands-on experience from internships to senior product delivery, and brings a practical knack for turning ML research into repeatable, observable production services.
9 years of coding experience
5 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Utah Valley University
Spanish