Summary
Matt Fair is a staff perception engineer and seasoned software leader with 14+ years building low-latency, mission‑critical systems across national labs, security, finance, robotics, and AI. He combines deep systems and embedded experience (STM32, ARM Cortex‑M, real‑time firmware and DroneCAN with <100µs intra‑module latency) with cloud‑native orchestration of large-scale ML workloads (Kubernetes, Ray) and production RAG/LLM pipelines. Matt has led cross‑functional teams to deliver real‑time telemetry, high‑throughput trading platforms, and deployed perception algorithms (EKF, SfM, SLAM) from research prototypes to operational systems. Comfortable from bare‑metal to distributed microservices, he emphasizes observability, predictable delivery, and rigorous debugging (eBPF, perf, gdb) to meet tight SLOs. Based in Austin, he pairs an entrepreneurial mindset—founding and shipping robotics and AI products—with experience managing multi‑million dollar programs and live deployments.
14 years of coding experience
24 years of employment as a software developer
BA, Computer Science, BA, Computer Science at University of Minnesota Morris
NDO, Computer Science, NDO, Computer Science at Stanford University