Dillon Mabry is a Senior AI Solutions Engineer with 11 years of experience building production-grade ML and data platforms across finance and aerospace. He blends hands-on software engineering, MLOps, and SRE practices—shipping feature stores, ML registries, and real-time decisioning services using Python, Java/Spring, Kubernetes/Openshift, and AWS. At Discover he led deployments yielding multimillion-dollar impact and helped architect core platform services like metadata registries and CI/CD automation; earlier roles at Bank of America focused on large-scale ETL, Airflow orchestration, and data lineage tooling. His academic foundation (MS in Analytics, Georgia Tech) complements practical expertise in time series forecasting, gradient boosting, and applied deep learning for energy and fraud use cases. Notably, he pairs platform-level thinking (vault-backed registries, MLFlow, observability integrations) with developer ergonomics—CLI tooling and reusable packages that accelerate model-to-production velocity. Based in Charlotte, he brings a pragmatic, cross-functional approach to turning complex data science workflows into reliable, auditable systems.
11 years of coding experience
10 years of employment as a software developer
Bachelor of Science Computer Science, Bachelor of Science Computer Science at University of North Carolina at Charlotte
Master of Science Analytics, Master of Science Analytics at Georgia Institute of Technology
Contributions:7 releases, 28 commits, 26 pushes in 2 months
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Dillon Mabry - Senior AI Solutions Engineer at Collins Aerospace