Chris Ahn

I’m a seasoned Senior Machine Learning Engineer & Data Scientist with over 9 years of experience building and deploying scalable AI/ML systems across healthcare, autonomous vehicles, e-commerce, and streaming media. I focus on delivering end-to-end machine learning pipelines—from data ingestion and model development to deployment and MLOps in production.

Most recently at Abridge (AI Health Startup), I led efforts to integrate large language models (LLMs) and multimodal AI into healthcare products. I spearheaded LLM-driven clinical assistant initiatives, reducing provider response times by 30% and architected a retrieval-augmented chatbot platform that drove a 40% increase in internal tool adoption.

I also standardize MLOps best practices while mentoring a small team, integrating external AI APIs securely and cutting model deployment cycle time by ~50% using AWS SageMaker, GCP Vertex AI, and MLflow. I built secure FastAPI endpoints for multimodal models integrated with EHR systems, ensuring HIPAA compliance and patient data privacy.

Earlier, at Scale AI, I built production-grade ML and data-centric pipelines for NLP, computer vision, and multimodal projects—co-developing Scale Nucleus, an enterprise dataset management and evaluation platform. Before that at Netflix, I developed recommendation systems and dynamic pricing models that improved CTR by 20% and customer lifetime value (LTV) by 15%, while optimizing Spark/SQL workloads to cut cloud compute costs by 25%.