Staff Machine Learning Engineer

Staff Machine Learning Engineer – Frontier AI / Clinical Intelligence AI Healthcare Startup | Real-World Clinical AI | Hybrid (San Francisco) We’re hiring a Staff ML Engineer (Frontier AI) to join a leading healthcare AI company building intelligent systems that improve clinical workflows at scale. Their platform powers real-time documentation, coding, and decision support across major health systems — operating in complex environments with messy EHR data, strict compliance constraints, and high accuracy + low latency requirements. You’ll own the hardest model quality problems and drive research that directly impacts real-world clinical outcomes. You’ll work on: Clinical AI models (coding, scribing, chart understanding) Learning loops from real-world feedback (clinician edits, audits) Long-context reasoning across patient records Retrieval, grounding, and clinical QA systems Optimisation across latency, cost, and performance What You’ll Do: Lead model research and drive architecture decisions Identify failure modes and ship end-to-end improvements Build systems that continuously improve from real-world data Apply techniques like RLHF, distillation, and model optimisation Collaborate across engineering, product, and domain teams What We’re Looking For: 5+ years in ML engineering or applied research Deep expertise in RL and deep learning Experience taking models from research → production Strong Python + PyTorch experience Track record of improving model performance in production Nice to have: Top-tier ML publications Experience with clinical or regulated data Background in RAG, long-context models, or reasoning systems This Role Is: Hybrid — San Francisco (3 days onsite) $250K–$350K base + equity