Summary
Joe Meiring is a Staff Applied AI Engineer in Austin with 14 years of experience building production-grade data and ML systems that move beyond prototypes into operational value. He has architected large-scale analytics platforms and ETL pipelines handling hundreds of billions of rows, productionized ML models for cybersecurity, and implemented RAG search workflows with vectors and LLMs. Comfortable across the stack, he pairs Python-first engineering (Flask, FastAPI, Spark, PyTorch) with cloud-native automation (AWS Step Functions, EMR, Lambda, Kubernetes) and a background in geospatial and HPC services. His career blends academic rigor鈥攁 PhD in Physics and postdoc research鈥攚ith hands-on product delivery at companies from TACC to SpyCloud and startups, which explains his fluency with scientific data, LiDAR/geospatial APIs, and interactive visualizations. Colleagues rely on him to turn complex datasets into deployable, auditable systems that accelerate reporting and decision-making. An understated strength is his ability to bridge research-grade algorithms and enterprise engineering to cut multi-day workflows down to hours.
13 years of coding experience
17 years of employment as a software developer
B.S. Physics, B.S. Physics at College of Charleston
PhD Physics, PhD Physics at University of South Carolina
Spanish, Italian