What are the responsibilities and job description for the Founding Forward-Deployed ML Engineer position at Clera?
About The Role
Join an early-stage healthtech company building rigorous, independent evaluation and validation infrastructure for 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 bridge benchmark performance and real-world clinical reliability. This is a high-impact, customer-facing role that shapes how AI is trusted and adopted in patient care.
What You'll Do
This is a hybrid, on-site role based in Sunnyvale, CA. Candidates should expect regular travel to hospital partner sites as part of the role.
Join an early-stage healthtech company building rigorous, independent evaluation and validation infrastructure for 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 bridge benchmark performance and real-world clinical reliability. This is a high-impact, customer-facing role that shapes how AI is trusted and adopted in patient care.
What You'll Do
- Build reproducible evaluation pipelines and validation workflows for medical imaging AI in clinical settings.
- Lead forward-deployed engagements, working on-site with hospital partners to integrate AI models into clinical workflows.
- Analyze model generalization, failure modes, and uncertainty to support clinical reliability assessments.
- Integrate ML models into clinical imaging systems and radiology pipelines (DICOM/PACS).
- Translate clinical needs into technical requirements and drive cross-functional projects to completion.
- Support regulatory submissions and clinical evaluations (FDA 510(k), De Novo pathways) and maintain related documentation.
- Ensure data privacy and regulatory compliance (HIPAA) across all ML deployments.
- Establish and maintain MLOps practices for deployment, monitoring, and evaluation using Python, PyTorch/TensorFlow, Docker, and Kubernetes.
- 2 years of Machine Learning or ML Engineering experience.
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent practical experience).
- Practical MLOps and model evaluation skills: reproducible pipelines, model validation/monitoring, and fluency with Python and common ML frameworks (PyTorch/TensorFlow, Docker, Kubernetes).
- Hands-on experience deploying ML models to cloud platforms (AWS, GCP, or Azure) with containerized environments and ML-focused CI/CD pipelines.
- Hands-on expertise in medical imaging workflows and integration (DICOM/PACS, radiology pipelines).
- Experience navigating healthcare data privacy and regulatory compliance (HIPAA, FDA considerations) in ML deployments.
- Experience supporting regulatory submissions and clinical evaluation processes (e.g., FDA 510(k) or De Novo pathways).
- Strong customer-facing skills: ability to communicate with clinical and industry partners, own engagements end-to-end, and drive cross-functional projects to completion.
- Willingness to travel to hospital sites and work on-site for customer deployments as needed.
- Salary range: $150,000 – $230,000 USD annually
- Early-stage equity opportunity as a founding team member
- Note: Visa sponsorship is not available for this role
This is a hybrid, on-site role based in Sunnyvale, CA. Candidates should expect regular travel to hospital partner sites as part of the role.
Salary : $150,000 - $230,000