Teams at Hippocratic AI

Own end-to-end AI data labeling and evaluation programs supporting frontier healthcare models. Responsibilities include designing annotation tasks and rubrics, managing clinician and expert rater workforces, overseeing vendors, building quality-control systems, tracking throughput and costs, and coordinating ML, engineering, clinical, and infrastructure teams. The role manages supervised, audio, conversational, preference, RLHF, and evaluation data pipelines while improving quality and delivery speed.

Owns the UX and interface design of an internal labeling and annotation tool. Responsibilities include redesigning workflows to improve efficiency and accuracy, prioritizing interface changes, defining performance metrics, applying gamification and behavioral psychology, managing reward and feedback mechanics, and partnering with technical product managers and engineering to deliver improvements.

Own the end-to-end reinforcement learning and on-policy distillation post-training pipeline for healthcare-focused large language models. Design RL methods, build reward models and verifiers, develop conversational healthcare simulations, automate post-training with agents, and conduct rigorous experiments. Collaborate with research, engineering, and clinical teams to improve model reasoning, safety, and alignment.