Research Scientist, Agent Post-Training, DeepMind
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Minimum qualifications:
- PhD in Computer Science, Machine Learning, or a related quantitative field, or equivalent practical experience.
- 2 years of experience with machine learning frameworks such as JAX, Flax, or PyTorch.
- Experience conducting research in reinforcement learning, tool use, or agentic systems.
Preferred qualifications:
- Experience publishing research in reinforcement learning, reinforcement learning from human feedback, or tool-use algorithms at machine learning venues.
- Experience working with large-scale distributed training infrastructure and scaling experiments.
- Research experience in systems design, code complexity, or working with large-codebase environments.
- Experience developing simple, scalable solutions for complex, open-ended research problems.
About the job
At DeepMind, we have built a unique culture and work environment where long-term ambitious research can flourish. We are seeking a highly motivated Research Scientist to join our team and contribute to groundbreaking fundamental research and deployment in large-scale agent post-training.
About us the Artificial Intelligence could be one of humanity’s most useful inventions. At DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
In this role, we are looking for a Research Scientist or Research Engineer that is keen to push the frontier of agentic tasks in post-training large language models. As part of the Gemini post-training team, you will have the chance to drive the research that makes up for the foundation of upcoming releases.
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.
Responsibilities
- Drive the research process for large-scale agent post-training from hypothesis formulation to delivery in the Gemini model recipe.
- Design and execute ablation studies to validate research hypotheses and accelerate experimental feedback loops.
- Communicate research findings, progress, and outcomes to the broader team through visualizations and reports.
- Develop research infrastructure and utilities for data analysis and model evaluations using standard engineering practices.
- Collaborate with other research scientists and engineers to maintain a regular feedback and communication loop.
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