Dillon Teal is a Software Engineer II and astrophysicist with a PhD in Astronomy and a decade of experience building cloud-native, testable systems for scientific research and data pipelines. He designs and ships scalable CI/CD frameworks, modular APIs, and cloud-based pipelines—reducing release lead times from months to hours—while working closely with mixed teams of scientists and engineers. His background in atmospheric and exoplanet modeling gives him deep domain expertise in scientific modeling and high-performance code in Python, Fortran, and C. At NOIRLab he helped extract reusable libraries from monolithic reduction systems and standardized contributor-facing CI templates to improve onboarding for community toolkits. A committed mentor and educator, he has taught at the university level and co-founded outreach initiatives to make science and software more accessible. He blends rigorous research instincts with pragmatic engineering to build durable tools that enable reproducible science.
10 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Astronomy, Doctor of Philosophy - PhD, Astronomy at University of Maryland
A function parsing and management library written in Python.
Contributions:16 releases, 9 reviews, 324 commits in 1 year 5 months
pythonmetaprogrammingparsingpython3parser
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Dillon Teal - Software Engineer II at NSF's NOIRLab