Jacob Hope is an Autonomy Engineer III with eight years of software engineering experience focused on bringing research-grade autonomy and high-performance computing into production. He blends machine-learning auto-tuning, GPU graph analytics, and parallel C++ (CUDA/MPI/OpenMP) expertise with practical systems work at SkyGrid, collaborating with FAA, NASA, Boeing, and academic partners to raise technical readiness for certified flight systems. A published researcher and SC19 ACM Student Research Competition semi-finalist, he has hands-on experience on supercomputers like TACC’s Lonestar 5 and a strong Python stack for ML, data wrangling, and visualization. He also has a proven track record as a STEM tutor and peer mentor, helping students bridge theory and practice while consistently making the Dean’s List. Comfortable shifting between low-level performance engineering and applied ML, Jacob brings both academic rigor and product-focused pragmatism to autonomy challenges.
8 years of coding experience
5 years of employment as a software developer
Bachelor of Science - BS Major in Computer Science Minor in Mathematics, Bachelor of Science - BS Major in Computer Science Minor in Mathematics at Texas State University
Computer Science, Computer Science at Austin Community College
originally forked from java-hello-world-with-gradle
Contributions:3 releases, 7 pushes, 1 branch in 2 months
kotlinjavagradlegradle-plugin
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