Rad AI
Machine Learning Research Manager
San Francisco - Onsite · Senior · Full-time
Sponsorship not specifiedDetected 98 days ago
Machine LearningDeep LearningPyTorchNLPLLMsRAGValuationPatient CareRadiologyResearchExperimental DesignLeadershipCommunicationCollaborationMentoring
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odds of building a lasting career here
28Risky
Cap-exempt (no lottery)0
Sponsors this role45
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
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About the role
- 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.
- If you're ready to shape the future of healthcare, we'd love to have you on our team!
Responsibilities
- 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
- Create strong cross-functional working rhythms with engineering, product, and clinical partners so research outputs are practical, trustworthy, and deployable
- 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
- 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
Requirements
- Strong hands-on experience with modern ML tooling such as PyTorch and common model training and evaluation workflows
Nice to have
- Experience with RAG, RLHF, GRPO, and other modern model training techniques
- 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
- This role is open to candidates located anywhere in the United States.
- 11 Paid Company Holidays
- Periodic team offsites
- For roles based outside the US, your recruiter can share more details
Compensation
- Annual company-wide offsite
Benefits
- Help the team train and evaluate advanced NLP and reasoning systems that work with clinical text, diagnostic criteria, reporting workflows, and other healthcare data
- 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
- Strong background in NLP and modern deep learning, especially in fine-tuning transformer-based systems and large language models
Company info
- 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.
- 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.
This listing is sourced directly from Rad AI's careers page and normalized into a canonical job model.