Medical AI Researcher
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About the Role Join a small, mission-driven team conducting rigorous, independent evaluations of medical imaging AI systems — bridging the gap between benchmark performance and real-world clinical reliability. As a Medical AI Researcher , you'll work directly with medical imaging companies preparing FDA submissions, owning customer engagements end-to-end: from defining evaluation questions to delivering evidence that informs go/no-go decisions. You'll combine strong ML skills with customer-facing judgment to characterize model behavior, generalization, and uncertainty in real-world clinical workflows. What You'll Do Lead end-to-end customer engagements — run meetings, define evaluation questions, and scope investigations. Design and execute investigations that characterize model behavior, generalization, failure modes, and remaining uncertainty. Analyze medical imaging workflows (DICOM/PACS, radiology pipelines) and translate findings into actionable evaluation evidence. Deliver clear, defensible reports and presentations for regulatory and internal audiences under tight timelines. Collaborate with customers and cross-functional teams to inform product strategy and go/no-go decisions. What We're Looking For Required: Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent practical experience). Hands-on expertise with medical imaging workflows and integration — DICOM/PACS, radiology pipelines, and integrating ML models into clinical systems. Proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow). Practical MLOps and model evaluation skills: building reproducible evaluation pipelines, model validation/monitoring, Docker, and Kubernetes. Several years of experience in ML evaluation or medical imaging AI. Nice to Have: Healthcare industry experience. Familiarity with regulatory considerations for medical AI, including FDA submissions such as 510(k) or De Novo. Compensation & Benefits Salary: $150,000 – $230,000 USD annually Visa sponsorship is not available for this role. Location This is a full-time, on-site role based in San Francisco, CA . Remote work is not available.
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