Rad AI
Senior ML Research Scientist
San Francisco - Onsite · Senior · Full-time
Sponsorship not specifiedDetected 57 days ago
PythonMachine LearningDeep LearningPyTorchNLPComputer VisionLLMsA/B TestingComplianceValuationElectrical EngineeringHIPAAPatient CareFDA RegulatoryRadiologyResearchCommunicationCollaborationPublic Speaking
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odds of building a lasting career here
28Risky
Cap-exempt (no lottery)0
Sponsors this role45
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
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About the role
- With one of the largest proprietary radiology report datasets in the world, our AI has helped uncover hundreds of new cancer diagnoses and reduced error rates in tens of millions of radiology reports by nearly 50%.
- Rad AI has secured over $140M in funding, including a recently oversubscribed Series C ($68M round) led by Transformation Capital, bringing our valuation to $528M.
- If you're ready to shape the future of healthcare, we'd love to have you on our team!
Responsibilities
- Own a multimodal ML work-stream from problem definition through experimentation, evaluation, deployment, and iteration.
- Work with image, report, and other clinical data to develop systems that are useful in real radiology workflows.
- Design rigorous evaluations that go beyond aggregate offline metrics, including clinically meaningful operating points, robustness, calibration, and performance across relevant data slices.
- Partner with engineering to productionize models, make practical system tradeoffs, and learn from performance after launch.
- Communicate research findings and technical decisions clearly through design documents, experiment reviews, and presentations to technical and clinical partners.
Requirements
- Experience owning substantial ML projects across the full lifecycle, from data and modeling through production delivery.
- Typically 4+ years of relevant applied ML research or engineering experience, or equivalent scope and impact.
Nice to have
- Familiarity with chest X-ray, CT, MRI, mammography, or other clinical imaging modalities.
- Experience evaluating models across patients, sites, scanner vendors, protocols, or other sources of distribution shift.
- Familiarity with clinical validation, FDA or HIPAA considerations, or other regulated and privacy-sensitive environments.
- Publications, open-source contributions, or other evidence of research credibility.
- You'll establish a strong understanding of the clinical problem, build a credible data and evaluation strategy, deliver models that perform reliably in practice, and help the team learn from real-world use.
- Over time, you'll help raise the quality of research and technical decision-making through strong experimentation, clear communication, and thoughtful mentorship.
- We value direct communication, intellectual honesty, strong ownership, and practical judgment.
- The best work here comes from people who can go deep technically, stay close to the clinical context, and make progress even when the problem and the path are not fully defined.
Compensation
- Annual company-wide offsite
Benefits
- At Rad AI, we're on a mission to transform healthcare with artificial intelligence.
- Our investors include Khosla Ventures, World Innovation Lab, Gradient Ventures, Cone Health Ventures, and others-all backing our mission to empower physicians with cutting-edge AI.
- Build and evaluate modern ML systems, including transformers, self-supervised learning, weak supervision, detection, localization, and segmentation.
- Strong applied experience in computer vision, NLP, or deep learning, with a track record of independently designing experiments, analyzing results, and turning findings into working systems.
Company info
- ABOUT RAD AI At Rad AI, we're on a mission to transform healthcare with artificial intelligence.
- Founded by a radiologist, our AI-driven solutions are revolutionizing radiology-saving time, reducing burnout, and improving patient care.
- Most recently, Rad AI was named to CNBC's Disruptor 50 https://www.cnbc.com/2025/06/10/2025-cnbc-disruptor-50-see-the-full-list-of-companies.html list, highlighting the innovation and momentum behind our mission.
This listing is sourced directly from Rad AI's careers page and normalized into a canonical job model.