Neal Debuhr is a Simulation Engineer and cloud-savvy systems practitioner with 10 years of experience blending HPC, simulation, and DevOps to deliver reliable, instrumented software systems. He has driven SRE, MLOps, and AI strategy work while building immutable, as-code test and production pipelines using Kubernetes, Docker, Jenkins, and cloud services (AWS/GCP). Neal pairs academic rigor from a Master’s in Modeling & Simulation with hands-on delivery across customer-facing solutions, internal productivity platforms, and research-grade HPC tooling. He has a track record of automating feedback loops and KPIs into visualization-driven decision engines, and has built discrete-event simulations and Selenium-based black-box test frameworks. Active in open source and research since 2018, he operates at the intersection of simulation, web3, and high-performance computing—bringing both product-focused pragmatism and research-informed depth. Based in New York, he also emphasizes technical training and process-driven improvements that scale across organizations.
10 years of coding experience
4 years of employment as a software developer
Certificate in Software Development and Programming, Certificate in Software Development and Programming at University of California, Berkeley
Master of Engineering, Modeling and Simulation, Master of Engineering, Modeling and Simulation at Arizona State University
Bachelor of Science in Mechanical Engineering, Bachelor of Science in Mechanical Engineering at University of Colorado Boulder
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