Research Scientist, Reinforcement Learning

London, United KingdomOn-site

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Responsibilities

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact.
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We're looking for talented Research Scientists to push forward fundamental research and technology in Artificial Intelligence, as part of our interdisciplinary and collaborative Reinforcement Learning team. About Us
Over the past decade, members of the RL team have been instrumental in building DQN, AlphaGo, Rainbow, AlphaZero, MuZero, AlphaStar, AlphaProof and Gemini.
As a Research Scientist, you'll use machine learning knowledge and technical know-how to innovate, drive research projects, as well as apply research to impactful problems.
Our projects span the full range of state-of-the-art machine learning and AI fields, including large language models, distributed machine learning techniques, and much more, but with an emphasis on reinforcement learning.
In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:
PhD in ML preferred, or equivalent practical experience.
Experience with RL for sequence models, post-training, preference-based learning, or agentic systems. •
Experience with modern research stacks (e.g., JAX/Flax or PyTorch) and scaling experiments.

DeepMind’s RL team is a long-standing and tight-knit team of collaborative scientists and engineers, led by Tom Schaul.
We tackle large scale research challenges in reinforcement learning.
We design, refine, and scale RL algorithms and deliver meaningful scientific or product impact.
You will be expected to implement code, run experiments, own results end-to-end, communicate them internally or externally, as well as collaborate with and empower others.