Advance memory and reasoning research at DeepMind in Toronto using deep learning, reinforcement learning, and continual learning architectures. Publish findings from rigorous experiments.

This Research Scientist role focuses on fundamental artificial intelligence research in Memory, Reasoning, and Continual Learning. You will initiate research directions using machine learning, natural language processing, reinforcement learning, and computational neuroscience. The work advances long-context attention, retrieval-augmented generation, continual learning, and multi-step reasoning frameworks.

Key Responsibilities:
Lead novel research directions in memory, reasoning, and continual learning
Design experiments testing hypotheses about model-based agents
Develop benchmarks for long-horizon memory and complex planning




Build infrastructure for high-capacity context windows and continuous training
Communicate findings through plots, writeups, and paper-ready narratives

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 expertise in memory, reasoning, Python, and continual learning to DeepMind’s Toronto research team.
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📌 Deepmind Research Scientist Memory Learning Toronto
🏢 Google
📍 Toronto