Google DeepMind builds Gemini and other frontier models from its London headquarters. They're hiring a Health Expert Lead for Gemini Data to shape high-quality health data that improves model performance, based in London on a hybrid basis. This data role sits within the UK's frontier AI sector.
Minimum qualifications:
- Master's degree in a Health-related field (e.g., Medicine, Public Health, Biomedical Informatics), or equivalent practical experience.
- Experience measuring the performance of Large Language Models (LLMs) or generative AI tools and optimizing them for healthcare or clinical use cases.
Preferred qualifications:
- Experience breaking down clinical workflows into concrete tasks, evaluation rubrics, and quality standards.
- Experience prioritizing AI capabilities and collaborating closely with cross-functional technical partners to unlock value for healthcare professionals.
- Demonstrated dual expertise bridging healthcare and AI, such as transitioning from a clinical practitioner into a technical machine learning role, or vice versa.
- Strong technical capabilities evaluating machine learning models, and applying Large Language Models to complex health workflows.
About the job
At DeepMind, we are expanding Gemini’s frontier AI capabilities into highly specialized professional domains. As a part of the Health Expert Lead, you will shape our foundational data strategy for the financial sector. In this role, you will apply your deep domain knowledge to map complex Health workflows, identify critical areas for model enhancement, and curate the high-quality data necessary to make Gemini the ultimate AI assistant for Health professionals.Artificial intelligence will be one of humanity’s most transformative inventions. At Google 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 diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
France: €130000 - €133000 (EUR) + 20% bonus target + equity + benefits
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about
benefits at Google.
Responsibilities
- Set the Health data strategy by mapping clinical workflows into a use-case taxonomy, and partnering with research to prioritize capabilities, data coverage, and sourcing pipelines.
- Create high-quality Health data by designing tasks and rubrics, and QA-ing datasets from vendors, customers, and synthetic pipelines for correctness, realism, and coverage.
- Steer data priorities using model failures by reproducing reported losses and stress-testing checkpoints on real workflows to identify missing clinical knowledge and false assumptions.
- Build Health evaluations by assessing industry benchmarks to measure data strategy success, and advise cross-team evaluation efforts on clinical coverage and realism.
- Scale expertise by recruiting and guiding Subject Matter Expert (SMEs), acting as the domain authority to enforce vendor quality, and converting expert contributions into usable training data.

About DeepMind
Google DeepMind is an AI research laboratory focused on building artificial general intelligence. Founded in London in 2010 by Demis Hassabis, Shane Legg, and Mustafa Suleyman, the company was acquired by Google in 2014 for approximately $660M. DeepMind pioneered breakthroughs including AlphaGo, the first program to defeat a world champion at Go, and AlphaFold, which solved the 50-year-old protein folding problem and has been used by over two million researchers worldwide. The lab remains headquartered in London with a large UK engineering presence and continues to push the boundaries of reinforcement learning, large language models, and scientific AI.
Stage: AcquiredLondon
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