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Senior Research Scientist, Gemini Release Evaluations, DeepMind

London, GB Full-time
Research ScientistAI ResearcherMachine Learning EngineerArtificial Intelligence EngineerData Scientist

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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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.


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


Learn more about benefits at Google.

Minimum qualifications:

  • PhD in Computer Science, a related field, or equivalent practical experience.
  • 2 years of experience leading a research agenda.
  • 1 year of experience in a data science field.
  • Experience with AI model training, testing, evaluation, and tuning processes, as well as LLM release cycles and timeline management.

Preferred qualifications:

  • 2 years of coding experience.
  • 1 year of experience leading research efforts and influencing other researchers.

Responsibilities:

  • Author research papers to share and generate impact of research results across function and in the research community.
  • Drive project work by defining the data structure, framework, design, and evaluation metrics for research solution development and implementation. Identify timelines and obtain resources needed.
  • Identify gaps in our existing release evals and create new SOTA datasets that push frontier models to their limits.
  • Help build a deeper understanding of the relationship between static evaluations and live production traffic.

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