Machine Learning Research Manager, Rad AI

• 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 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 development 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

Desirable

• We’re looking for a Machine Learning Research Manager to lead a dedicated, 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 hands on and being 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 applied and clinical researchers, 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, 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 build 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