Health Expert Lead, Gemini Data, DeepMind

Google LLC; Greater London; On-site; GBP 140,000 - 180,000; Full time

Job summary

Google DeepMind is expanding Gemini’s frontier AI capabilities to health professionals. You will shape foundational data strategy for health workflows, map complex clinical tasks, and curate training data to enable the Gemini AI assistant for health professionals.

You will design tasks and rubrics, QA datasets from vendors and synthetic pipelines, and drive data quality and clinical realism across multiple health domains. Strong collaboration with cross-functional partners is essential.

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.

Responsibilities

• Set the Health data strategy by mapping clinical workflows into a use-case taxonomy, and prioritizing data 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.

Skills

LLM evaluation

Healthcare AI

Cross-functional collaboration

Education

Master's degree in Health-related field

Job description

corporate_fare DeepMind place London, UK ; Paris, France ; +1 more

info_outline X For Paris: Google welcomes people with disabilities. Note: By applying to this position you will have an opportunity to share your preferred working location from the following: London, UK; Paris, France; Mountain View, CA, USA.

• 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.

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 .

• 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.

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