Join a healthtech company conducting rigorous, independent evaluations of medical imaging AI systems — bridging the gap between benchmark performance and 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 practical ML skills with customer-facing judgment to characterize model behavior, generalization, and uncertainty in real-world clinical workflows.
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 go/no-go decisions and drive impact on product strategy.
Required: Hands-on expertise in medical imaging workflows and integration (DICOM/PACS, radiology pipelines) and integrating ML models into clinical systems.
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field — or equivalent practical experience.
Several years of experience in ML evaluation or medical imaging AI.
Practical MLOps and model evaluation skills: building reproducible evaluation pipelines, model validation/monitoring, and proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow).
Familiarity with Docker and Kubernetes.
Nice to have: Experience with regulatory considerations for medical AI (FDA submissions such as 510(k) or De Novo).
Healthcare industry experience preferred.
Salary range: $150,000 – $230,000 USD annually. Please note that visa sponsorship is not available for this role.
This is an on-site role based in San Francisco, CA. Candidates must be available to work from the San Francisco office.