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United States
Hybrid
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!
We’re looking for a Machine Learning Research Manager to lead a small, high-impact team of applied and clinical researchers working at the intersection of clinical AI, language modeling, and radiology.
This is a player-coach role for someone who loves developing people, setting technical direction, and staying close to the work. You’ll help shape how our research organization scales while partnering deeply with clinicians, engineers, and product leaders to bring high-value ideas into production.
Directly manage and mentor a small team of research scientists, helping them grow in scope, judgment, execution, and communication
Drive research productivity by clarifying priorities, unblocking work, and creating a high-trust, high-accountability team environment
Stay close to the technical work as a player-coach by guiding problem framing, experimental design, training and evaluation strategy, and tradeoff decisions across multiple research efforts
Partner closely with radiologists, clinical experts, engineers, and product leaders to identify the highest-leverage research opportunities and translate them into production-scale systems
Help the team train and evaluate advanced NLP and reasoning systems that work with clinical text, diagnostic criteria, reporting workflows, and other healthcare data
Create strong cross-functional working rhythms with engineering, product, and clinical partners so research outputs are practical, trustworthy, and deployable
Raise the bar on research quality, reproducibility, and communication across the team
Stay current on relevant machine learning advances and help the team thoughtfully integrate new methods when they materially improve customer and clinical outcomes
MS or PhD in Computer Science, Machine Learning, Computational Linguistics, Biomedical Informatics, or a related quantitative field, or equivalent practical experience
6+ years of applied ML research experience, with a track record of taking work from idea to production impact
Prior people management experience, or clear evidence of operating as a de facto team lead for multi-person research efforts, with strong coaching and prioritization skills
Strong background in NLP and modern deep learning, especially in fine-tuning transformer-based systems and large language models
Experience applying ML to hard real-world problems where ambiguity, data quality, and operational constraints matter
Strong hands-on experience with modern ML tooling such as PyTorch and common model training and evaluation workflows
Demonstrated ability to collaborate closely with domain experts and cross-functional stakeholders, especially in environments where trust, iteration speed, and communication quality matter
Excellent written and verbal communication skills, with the ability to guide senior researchers while also aligning non-technical partners around research direction and tradeoffs
Experience working in healthcare, clinical AI, biomedical ML, or other regulated, privacy-sensitive environments
Experience with RAG, RLHF, GRPO, and other modern model training techniques
Experience with radiology, clinical documentation, medical terminology, or clinician-facing workflows
Experience deploying LLM or NLP systems in production settings
Experience contributing to research culture through mentorship, technical standards, or organizational leadership
Familiarity with cloud-based ML workflows and modern research infrastructure
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 and be sure to follow us on LinkedIn to stay up to date!
Location Details:
For roles listed as San Francisco - Onsite:
This role will be based in our San Francisco office and we expect employees to work onsite four days per week. The remaining time may be worked remotely or onsite, depending on team and business needs.
For roles listed as United States - Remote:
This role is open to candidates located anywhere in the United States.
For roles listed as San Francisco - Onsite + United States - Remote:
We will prioritize candidates who can work onsite four days per week in San Francisco, while also considering remote candidates located anywhere in the United States.
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
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.
