Machine Learning Research Manager

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 https://www.radai.com/news/auntminnie-recognizes-rad-ai-omni-reporting-as-2023s-best-new-radiology-software, and ranked by Deloitte https://www2.deloitte.com/us/en/pages/technology-media-and-telecommunications/articles/fast500-winners.html 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 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. 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 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. WHAT YOU’LL BE DOING - 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 WHO WE’RE LOOKING FOR - 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 NICE TO HAVE - Experience working in healthcare, clini