Summary
Logan Howard is a machine learning engineer with 11 years of experience building fraud, abuse, and trust-and-safety systems for high-growth platforms in the Bay Area. He currently works on trust & safety ML at Anthropic after leading anti-fraud machine learning efforts for Stripe Radar. A UC Berkeley EECS graduate, he brings a blend of research and product experience from internships and research roles at Atlassian and Berkeley, plus early startup engineering and leadership from Fremont Robotics and FreshPay. Logan is skilled at moving models from prototype to production in high-throughput, risk-sensitive environments and has deep practical experience in transaction fraud detection and abuse prevention. He combines technical rigor with product-minded engineering, often focusing on reliability, real-time feature pipelines, and operationalizing ML for safety-critical applications. Based in San Francisco, he balances a research-informed approach with hands-on systems integration that helps teams ship robust ML solutions.
11 years of coding experience
6 years of employment as a software developer
Bachelor of Science (B.S.) Electrical Engineering and Computer Science, Bachelor of Science (B.S.) Electrical Engineering and Computer Science at University of California, Berkeley
High School General Education, High School General Education at Fremont High School