In the DeepMind's Frontier Health team, you will build agentic, multimodal AI systems that meaningfully assist in healthcare. You will develop novel methods at the intersection of large language models, reinforcement learning, and clinical medicine, contributing to publications while shaping real-world products. As a passionate researcher, you will grow in a fast-moving, collaborative environment spanning machine learning, clinical expertise, and product development.
Artificial intelligence will be one of humanity’s most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
We are pushing the boundaries across multiple domains. Our global teams offer learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
The US base salary range for this full-time position is $174,000-$252,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Develop reinforcement learning pipelines (e.g., RLHF, GRPO, reward modeling) to align AI systems with strict clinical quality and safety standards.
- Build evaluation frameworks, and human-expert grading protocols to benchmark AI on realistic clinical scenarios.
- Identify key problems, formulate hypotheses, run scalable experiments, and publish findings at venues.
- Partner closely with clinicians, product teams, and ML researchers to translate theoretical research into tangible healthcare impact.
- Design and evaluate novel techniques for medical AI, focusing on agentic clinical reasoning, structured tool use, and multimodal understanding (text, image, audio/video).
Qualifications
Minimum qualifications:
- PhD degree in Computer Science, a related field, or equivalent practical experience.
- 2 years of experience leading a research agenda.
- One or more scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).
Preferred qualifications:
- Experience collaborating with domain experts or clinicians, and interest in responsible AI (e.g., safety).