Research Scientist, Gemini Data, DeepMind Ajouter aux favoris

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X For France applicants:
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: Paris, France; Mountain View, CA, USA .

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 the job

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 .

Responsibilities

• 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.

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