Staff ML Research Scientist

About Rad AI

At Rad AI were on a mission to transform healthcare with artificial intelligence. Founded by a radiologist our AI-driven solutions are revolutionizing radiologysaving 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 othersall 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 CNBCs Disruptor 50 list highlighting the innovation and momentum behind our mission.

If youre ready to shape the future of healthcare wed love to have you on our team!

Why Join Us

Were looking for a Staff Machine Learning Research Scientist to help define and drive Rad AIs next generation of applied research in NLP and clinical AI.

We work across LLMs retrieval representation learning speech and multimodal modeling and we care as much about evaluation and reliability as we do about state-of-the-art results. You will have scope ownership and a direct line from research to product.

Youll collaborate closely with clinicians engineers and product leaders to translate foundational research into production-scale systems that improve outcomes for doctors and patients alike. As we grow you will help shape standards for model quality safety and observability and contribute to strategic initiatives that include computer vision and vision-language work.

What Youll Do:

• 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.

• Build evaluation that matters: link offline metrics to online outcomes; define thresholds monitoring and rollback.

• Partner to deliver with engineering and productand when relevant clinicians/domain expertsto align data success criteria and timelines.

• Raise the bar by mentoring peers and codifying standards for reliability safety and documentation.

• Improve the platform (data training serving observability) to speed iteration and ensure reproducibility.

• Explore new directions with computer vision/vision-language work as a nice-to-have for future strategic initiatives.

What Were 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 offlineonline 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).

• System thinking: can choose methods based on constraints design for observability and rollback and document decisions clearly.

• Collaborative communicator who writes crisp design docs and explains complex ideas to non-specialists; comfortable mentoring peers.

Preferred Qualifications

• Health data familiarity including EHR or imaging

• Experience in one or more areas: clinical NLP or LLMs computer vision speech retrieval or multimodal modeling.

• Shipped measured models in production with monitoring and clear rollback; external or multi-site validation is a plus.

• Workflow integration with EHR RIS PACS or reporting systems; PowerScribe or Dragon exposure helpful.

• Strong evaluation practices: calibration slice analysis and ablations

• Safety and governance in sensitive domains including PHI handling and HIPAA or FDA-adjacent environments.

• Technical mentorship and contributions to team research culture; publications or impactful open-source work.

• Practical tooling: PyTorch plus modern ML ops tools such as MLflow Databricks Ray or Triton.

Why This Matters:

Radiologists are the invisible backbone of modern medicine. Every diagnosis every surgery every treatment plan begins with their interpretations. Yet theyre often overwhelmed by cognitive load repetitive tasks and administrative overhead.

At Rad AI were using ML to change thatbuilding intelligent systems that understand medical context streamline documentation and amplify human expertise.

Youve 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.

We welcome applicants from across the United States with a preference for this role to be based in our new San Francisco office.

Join our world-class team as we build and deploy AI solutions that empower physicians and transform patient caremaking 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 youre passionate about driving innovation and delivering impactful healthcare solutions wed love to hear from you!

To learn more about what its like to work at Rad AI visit 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 @ or

Required Experience:

Staff IC