Stirling Waite is a Lead Machine Learning Operations Engineer with 11 years of engineering experience and 8+ years focused on MLOps and AI platform development. He has built ML teams and scalable platforms from the ground up, delivering production-grade CI/CD pipelines, distributed training/serving on Ray and EKS, and cost-saving cloud automation that shaved six figures over time. His background spans fast-moving startups and large enterprises where he modernized monoliths into microservices, implemented observability with Grafana/Prometheus, and operationalized models from XGBoost to cutting-edge LLMs. Based in Salt Lake City, he pairs practical software engineering (FastAPI, Terraform, Databricks, SageMaker) with data science rigor from Harvard Extension’s Software Engineering program. Notably, he has hands-on experience building feature stores and large-scale pipeline infrastructure that served millions of users and processed billions of events. Stirling blends leadership, deep systems knowledge, and a proven track record of turning experimental ML into reliable, cost-efficient production services.
11 years of coding experience
15 years of employment as a software developer
Master of Science - MS Engineering: Software Engineering, Master of Science - MS Engineering: Software Engineering at Arizona State University
Bachelor of Science (BS) Computer Science, Bachelor of Science (BS) Computer Science at Weber State University
Master of Liberal Arts Software Engineering, Master of Liberal Arts Software Engineering at Harvard Extension School
Associate of Applied Science (AAS) Computer and Information Systems Security/Information Assurance, Associate of Applied Science (AAS) Computer and Information Systems Security/Information Assurance at Salt Lake Community College
Contributions:8 PRs, 41 pushes, 1 branch in 1 month
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