Summary
Daniel Antohe is a physician-turned-technologist who leads ML and AI engineering for 24/7 healthcare systems, bringing over two decades at the intersection of medicine, cloud platforms, and machine intelligence. He specializes in turning cutting-edge AI—LLMs, NLP, and agentic systems—into hardened, low-latency, auditable production platforms that run under real-world constraints like live voice streams, HIPAA, cost ceilings, and zero-tolerance downtime. At AMC Health he architects and operates multi-agent real-time pipelines that transcribe conversations, detect clinical signals, and generate structured artifacts clinicians rely on in production. His background ranges from biomedical NLP research and HL7/QRDA clinical quality systems to building enterprise MLOps and AWS-native HIPAA-compliant platforms, giving him rare fluency across clinical, regulatory, and infrastructure domains. He’s motivated by high-stakes problems where prototypes fail and reliability matters—he doesn’t prototype; he ships resilient systems that survive contact with reality.
11 years of coding experience
21 years of employment as a software developer
Master in Science of Computer Science, Intelligent Systems, Master in Science of Computer Science, Intelligent Systems at The University of Texas at Dallas
Graduate, Information Tecahnology - Computer Scinece, Graduate, Information Tecahnology - Computer Scinece at Technical University of Cluj-Napoca (Universitatea Tehnică din Cluj-Napoca)
Machine Learning Engineering (Deep Learning, ML, AI) Fellowship, Machine Learning Engineering (Deep Learning, ML, AI) Fellowship at Springboard
Doctor of Medicine (MD), General Medicine, Doctor of Medicine (MD), General Medicine at Iuliu Haţieganu University of Medicine and Pharmacy Cluj-Napoca
English, Romanian