Modern radiology AI for reporting, impressions and follow-up. Reduce cognitive burden, improve report quality and help radiologists work faster. Backed by Khosla.
About the role
Own end-to-end applied research : frame the problem, design experiments, ship to production, and monitor impact against real-world metrics. Set technical direction across LLMs, retrieval, and multimodal; run ablations/error analysis that change product decisions.
What they're looking for
- MS or PhD (or equivalent research experience) in Computer Science, Electrical Engineering, Computational Linguistics, Biomedical Informatics, or related quantitative field
- 7+ years of applied ML research experience (or PhD + 5 years, or equivalent evidence of Staff-level impact)
- Depth in one or more areas: LLMs and NLP, computer vision, speech, recommendation/ranking, retrieval, or multimodal modeling
- Strong experimental rigor: clear hypothesis framing, offline→online linkage, calibration and stratified analyses, ablations that influence decisions
- Proven ability to take models to production
- Hands-on with modern tooling: PyTorch and common experiment/ops tools (for example MLflow, Databricks, Ray, or similar)
More about this role
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. 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. 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.
Our latest advancements in generative AI are used by thousands of radiologists daily, supporting more than one-third of radiology groups and healthcare systems and nearly 50% of all medical imaging in the U.S. at partners including Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health.
Recognized as one of the most promising healthcare AI companies by CB Insights and...
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