Summary
Samuel Andersen is a Staff Engineer based in San Francisco with 11 years of experience translating executive strategy into production-grade AI/ML and cloud infrastructure for large enterprise customers. At Google he leads deployment of accelerators like GPU and TPU at mega-scale, owns a custom CI/CD stack integrating JAX and TensorFlow, and dives into low-level Triton/Pallas kernel debugging to unblock high-impact ML workloads. His background spans systems engineering, analytics automation, and solutions architecture at Cisco, Meraki, and Red Hat, where he built tooling that tied technical work to measurable business impact. Known for turning stakeholder requirements into concrete implementations, he combines hands-on kernel- and infra-level problem solving with a track record of shipping cross-functional processes and observability tooling. An uncommon strength is his ability to operate across executive, research, and SRE audiences, making him a bridge between cutting-edge ML research and reliable, scalable production systems.
11 years of coding experience
6 years of employment as a software developer
Bachelor’s Degree B.S. Computer Science, Bachelor’s Degree B.S. Computer Science at The University of North Carolina at Chapel Hill
The Chinese University of Hong Kong (CUHK)
Portuguese, Spanish, Chinese, English, French