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.
What You’ll Do
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Lead end-to-end customer engagements: run meetings, define evaluation questions, and scope investigations.
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Design and execute investigations that characterize model behavior, generalization, failure modes, and remaining uncertainty.
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Analyze medical imaging workflows (DICOM/PACS, radiology pipelines) and translate findings into actionable evaluation evidence.
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Deliver clear, defensible reports and presentations for regulatory and internal audiences under tight timelines.
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Collaborate with customers and cross-functional teams to inform go/no-go decisions and drive impact on product strategy.
What We’re Looking For
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Required: Hands-on expertise in medical imaging workflows and integration (DICOM/PACS, radiology pipelines) and integrating ML models into clinical systems.
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Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field — or equivalent practical experience.
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Several years of experience in ML evaluation or medical imaging AI.
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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).
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Familiarity with Docker and Kubernetes.
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Nice to have: Experience with regulatory considerations for medical AI (FDA submissions such as 510(k) or De Novo).
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Healthcare industry experience preferred.
Compensation & Benefits
Salary range: $150,000 – $230,000 USD annually. Please note that visa sponsorship is not available for this role.
Location
This is an on-site role based in San Francisco, CA. Candidates must be available to work from the San Francisco office.