Summary
Nathan Marks is an AI software engineer and Stanford MS student with nine years of hands-on experience building production software and research systems across healthcare, compliance, and conversational AI. He currently develops AI systems at Accordance after co-founding Cadence AI, and has a track record of shipping engineering work at organizations such as Salesforce and Mayo Clinic as well as contributing research on dialogue error recovery in Stanford’s Open Virtual Assistant Lab. Comfortable across Java, Python, GUI and high-dimensional medical imaging pipelines, he blends applied machine learning and NLP with practical software engineering for regulated and clinical domains. Nathan is drawn to intersections of AI with medicine, energy, sustainability, and linguistics, and brings a curious maker’s mentality—hinted by his playful GitHub handle “Kachow”—to rigorous, real-world problems.
9 years of coding experience
2 years of employment as a software developer
High School Diploma, High School Diploma at Century Senior High School
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Stanford University
English, Spanish