Source description
About the role
We are a venture-backed, early-stage healthtech startup focused on independent, rigorous evaluation of medical imaging AI systems — bridging the gap between benchmark performance and real-world clinical reliability. We work with medical imaging companies preparing FDA submissions, providing the evidence infrastructure they need to make confident go/no-go decisions throughout the product lifecycle.
As a Medical AI Researcher, you will own customer engagements end-to-end — from defining evaluation questions to delivering defensible evidence for regulatory and internal audiences. You'll combine strong ML skills with customer-facing judgment to deeply understand model behavior, generalization, and uncertainty in clinical workflows.
Note: Visa sponsorship is not available for this role.
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 go/no-go decisions and drive impact on product strategy.
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.
-
Several years of experience (1–7 years) in ML evaluation or medical imaging AI.
-
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.
-
Nice to Have:
-
Prior healthcare industry experience.
-
Familiarity with regulatory considerations for medical AI, including FDA submission pathways such as 510(k) or De Novo.
-
Experience communicating technical findings to non-technical or regulatory stakeholders.
Compensation & Benefits
-
Salary: $150,000 – $230,000 per year, depending on experience.
-
Equity participation in a fast-growing, venture-backed startup.
-
High-impact, highly visible role at a small, mission-driven team.
LOCATION
This is a full-time, on-site role based in San Francisco, CA. Remote work is not available for this position.
More at Clera
Related open roles
Senior Platform Engineer (Kubernetes)
San Francisco Bay Area · Onsite
Founding Engineer – ML Research
Remote
Founding Engineer - ML Research
Remote
Neuroscience PhD – Inference Modelling (Founding Role)
San Francisco Bay Area · Onsite
Medical AI Researcher
San Francisco Bay Area · Onsite
AI/ML Engineer
San Francisco Bay Area · Onsite
