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Google

Research Scientist, Gemini Data, DeepMind

Google · DeepMind

Paris

Machine learning

Last seen 1mo ago

Posted
2mo ago

Posted on 6 July 2026

Workplace
Not specified

Work model not stated

Salary
Not disclosed

Salary range not shared by the company

Visa sponsorship
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This role has closed 1mo ago ago. It's kept as a record — see Google's open roles or the similar live roles below.

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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: €104000 - €106000 (EUR) + 15% bonus target + equity + benefits

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Conduct careful empirical research to validate novel research ideas to improve the performance of Gemini models.

Develop strong intuitions grounded in data scaling laws and theoretical insights that can lead to research breakthroughs and new model capabilities.

Propose data curation, generation, and evaluation solutions to address model limitations.

Propose, build, and rapidly prototype new ideas based on team needs.

Collaborate closely with the wider Gemini team, including the Model, Infrastructure, and Post-Training teams.

Minimum qualifications:

PhD degree in Computer Science, a related field, or equivalent practical experience.

2 years of experience in Large Language Model (LLM) modeling, including pre-training or fine-tuning.

Preferred qualifications:

Experience with JAX or similar distributed training frameworks.

Experience with running large-scale data processing pipelines.

Experience collaborating on or leading applied research projects.

About Google

Google runs core product engineering out of London, Dublin, Zurich, Warsaw and Munich — not support functions. Zurich is one of its largest engineering sites anywhere, and Warsaw has grown substantially. The bar is high and the process is long, but these are genuine product teams.

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