About the Role
This is a founding-team opportunity at a small, fast-moving healthtech AI company building evidence infrastructure for safety-critical medical imaging AI. As a Founding Forward-Deployed ML Engineer, you will sit at the intersection of research, product deployment, and clinical operations — working directly with hospital partners to evaluate and deploy medical imaging AI in real-world clinical settings.
You will play a central role in bridging the gap between benchmark performance and clinical reliability, translating AI models into trusted tools for patient care. This is a high-ownership, high-impact role suited to someone who is equally comfortable writing code, navigating clinical environments, and driving cross-functional projects to completion.
Work arrangement: Hybrid, on-site in Sunnyvale, CA. Travel to hospital partner sites required as needed.
Visa sponsorship: Not available.
What You'll Do
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Build reproducible evaluation pipelines and validation workflows for medical imaging AI in clinical settings.
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Lead forward-deployed engagements by working on-site with hospital partners to integrate models into clinical workflows.
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Analyze model generalization, failure modes, and uncertainty to inform clinical reliability assessments.
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Integrate ML models into clinical imaging systems and radiology pipelines (DICOM/PACS).
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Translate clinical needs into technical requirements and drive cross-functional projects through to completion.
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Support regulatory submissions and clinical evaluations (FDA pathways such as 510(k) and De Novo) and maintain related documentation.
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Ensure data privacy and regulatory compliance (HIPAA) across all ML deployments.
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Establish and maintain MLOps practices for deployment, monitoring, and ongoing evaluation.
What We're Looking For
Required (dealbreakers):
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2+ years of Machine Learning / Engineering experience.
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Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field — or equivalent practical experience.
Required skills & experience:
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Hands-on expertise in medical imaging workflows and integration: DICOM/PACS, radiology pipelines, and integrating ML models into clinical systems.
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Practical MLOps and model evaluation skills: building reproducible evaluation pipelines, model validation/monitoring, and proficiency with Python and common ML frameworks (PyTorch / TensorFlow, Docker, Kubernetes).
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Hands-on experience deploying ML models to cloud platforms (AWS, GCP, or Azure) with containerized environments and ML-focused CI/CD pipelines.
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Experience navigating healthcare data privacy and regulatory compliance (HIPAA, FDA considerations) in ML deployments.
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Experience supporting regulatory submissions and clinical evaluation processes (e.g., preparing evidence for FDA 510(k) or De Novo pathways).
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Strong customer-facing skills: ability to communicate with clinical and industry partners, own engagements end-to-end, and drive cross-functional projects to completion.
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Willingness to travel to hospital sites and work on-site for customer deployments as needed.
Compensation & Benefits
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Base salary: $150,000 – $230,000 USD annually, depending on experience.
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Early-stage equity opportunity as a founding team member.
Location
Sunnyvale, California, USA. Hybrid on-site role with travel to hospital partner sites as required. Remote work is not available for this position. Visa sponsorship is not offered.
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