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. 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 AuntMinnie, and ranked by Deloitte as the 19th fastest-growing company in North America, we are building AI-powered solutions that make a real impact. Most recently, Rad AI was named to CNBC’s Disruptor 50 list, highlighting the innovation and momentum behind our mission.
If you’re ready to shape the future of healthcare, we’d love to have you on our team!
Why Join Us?
We're looking for a Staff Machine Learning Research Scientist to help define and drive Rad AI's next generation of applied research in NLP and clinical AI.
The ideal candidate brings deep experience in ML and medical AI. You should be comfortable with medical literature, clinical terminology, and the nuanced decision-making criteria doctors use every day.
You'll collaborate closely with clinicians, engineers, and product leaders to translate foundational research into production-scale systems that improve outcomes for doctors and patients alike.
What You'll Do:
Lead high-impact ML research projects from concept to deployment, focused on clinical NLP and reasoning systems.
Define the technical direction of research initiatives within your product area; identifying opportunities to apply state-of-the-art models to real-world radiology workflows.
Collaborate deeply with radiologists and clinical experts to understand diagnostic reasoning patterns, report structures, and clinical decision-making criteria—then encode that understanding into robust ML systems.
Architect and evaluate models that integrate structured and unstructured medical data (clinical notes, diagnostic criteria, patient context) to enhance diagnostic reasoning and reporting accuracy.
Build NLP systems that can parse, reason over, and generate clinically accurate content using medical terminology and ontologies.
Mentor and guide other researchers in experimental design, model reproducibility, and technical communication.
Advance research infrastructure by contributing to data pipelines, training frameworks, and model evaluation tooling.
What We're Looking For:
MS or PhD (or equivalent research experience) in Computer Science, Electrical Engineering, Computational Linguistics, Biomedical Informatics, or related quantitative field.
6+ years of applied ML research experience (industry or academia).
Proven experience building NLP or ML systems for healthcare, clinical documentation, or biomedical applications— You should have shipped models that work with clinical text, radiology reports, EHRs, medical literature, or similar medical data.
Demonstrated fluency with medical terminology and clinical reasoning—you should be able to read and understand radiology reports, parse diagnostic criteria, and grasp how radiologists formulate clinical decisions.
Track record of successful collaboration with clinicians—you've worked directly with physicians, radiologists, or clinical researchers to understand requirements, validate models, and iterate based on medical domain expertise.
Deep expertise in NLP and modern deep learning architectures—particularly transformers and large language models.
Strong engineering skills with modern ML frameworks such as PyTorch.
Demonstrated ability to take ML models from research to production in complex, data-rich environments.
Exceptional written and verbal communication skills—able to explain complex technical ideas to cross-functional partners and synthesize clinical domain knowledge into research directions.
Preferred Qualifications
Experience with medical named entity recognition, clinical text classification, information extraction, report generation, or diagnostic reasoning systems.
Prior work modeling clinical decision-making logic, differential diagnosis, or impression synthesis.
Familiarity with medical data standards (DICOM metadata, HL7/FHIR) and healthcare NLP corpora.
Clinical background (MD, DO) or formal training in medical informatics, computational biology, or health systems.
Experience working specifically in radiology, diagnostic imaging workflows, or medical reporting systems.
Track record of technical mentorship and contribution to broader research culture.
Experience in regulated or privacy-sensitive domains (HIPAA, FDA, etc.).
Publications in healthcare AI, clinical NLP, or biomedical informatics venues.
Why This Matters:
Radiologists are the invisible backbone of modern medicine. Every diagnosis, every surgery, every treatment plan begins with their interpretations. Yet they're often overwhelmed by cognitive load, repetitive tasks, and administrative overhead.
At Rad AI, we're using ML to change that—building intelligent systems that understand medical context, streamline documentation, and amplify human expertise.
You've already seen how AI can transform healthcare. Now help us push it further.
Join us in shaping how AI supports the next generation of medical professionals.
Join our world-class team as we build and deploy AI solutions that empower physicians and transform patient care—making a meaningful impact on millions of lives. Driven by our mission, we prioritize transparency, inclusion, and close collaboration, bringing together exceptional people to revolutionize healthcare. If you're passionate about driving innovation and delivering impactful healthcare solutions, we'd love to hear from you!
To learn more about what it's like to work at Rad AI, visit https://www.radai.com/life-at-rad-ai
For US-Based Full-Time Roles, Rad AI offers a variety of benefits, including:
Comprehensive Medical, Dental, Vision & Life insurance
HSA (with employer match), FSA, & DCFSA
401(k)
11 Paid Company Holidays
Location Flexibility (Remote-first company!)
Flexible PTO policy
Annual company-wide offsite
Periodic team offsites
Annual equipment stipend
For roles based outside the US, your recruiter can share more details
At Rad AI, we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
Please be vigilant regarding job scams. We advise all candidates to apply directly through our official careers page. Our recruiters will use email addresses with the domain @radai.com or no-reply@ashbyhq.com.
