Summary
Robert Christensen is a senior software engineer with 13 years of experience building scalable machine learning platforms and systems engineering solutions, most recently at Splunk after a long tenure at Visa. He specializes in optimizing large-scale ML training and deployment—cutting training times from weeks to days—while designing low-latency online feature generation and priority-based scheduling on Kubernetes. Skilled in Python, TensorFlow, C++, and distributed systems, he focuses on enabling data scientists with libraries, tooling, and infrastructure that make experiments efficient and secure over sensitive data. His work blends research experience from the University of Utah and internships at Microsoft with practical production engineering, including building windowed aggregation and feature-understanding tools that expose model risk. Based in Lehi, Utah, he’s a systems-first engineer who quietly accelerates ML teams by turning data-science ideas into reliable, high-throughput pipelines.
13 years of coding experience
13 years of employment as a software developer
Computer Science, Computer Science at Snow College
The University of Utah