Advance memory and reasoning research at Google DeepMind using machine learning, continual learning, and large-scale experimentation. Publish findings from fundamental artificial intelligence research.

This Research Scientist position focuses on Memory, Reasoning, and Continual Learning. You will develop architectures, test model-based agents, and study non-stationary environments. The work spans long-context attention, Retrieval-Augmented Generation, and complex planning. Research findings will support scientific discovery and product innovation.

Key Responsibilities:

- Lead research directions in memory, reasoning, and continual learning
- Design end-to-end experiments and test research hypotheses
- Develop benchmarks for memory, generalization, and planning




- Build infrastructure for context windows and continuous training
- Communicate findings through plots, writeups, and papers

Requirements:

- PhD or equivalent practical experience in a related technical field
- Two years of artificial intelligence research experience with publications
- Experience with deep learning, reinforcement learning, NLP, or continual learning
- Python and JAX, TensorFlow, or PyTorch experience
- Experience designing algorithms, running experiments, and analyzing results

Apply research, experimentation, and publication skills to advance memory, reasoning, and continual learning at Google DeepMind.

📌 Research Scientist Memory Reasoning AI (Toronto)
🏢 Google DeepMind
📍 Toronto