Research Scientist, GenAI, DeepMind

Role Overview

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Responsibilities

• Define and lead strategic, high-impact research programs advancing state-of-the-art artificial intelligence models, algorithms, and theory.
• Provide technical leadership across multi-disciplinary research pods, guiding technical directions, experimental design, and execution.
• Publish groundbreaking research findings in peer-reviewed artificial intelligence and machine learning conferences and scientific journals.
• Collaborate closely with software engineering, infrastructure, and product teams to translate foundational research advances into production-grade systems and platform capabilities. Mentor, coach, and guide early-to-mid-career research scientists and engineers, fostering a culture of scientific excellence and innovation.
• Advocate responsible AI development, ensuring safety, alignment, ethics, and are integrated into all research initiatives from inception.

Requirements & Qualifications

Minimum qualifications:

• PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Computational Neuroscience, or a related quantitative scientific discipline, or equivalent practical research experience.
• Experience in leading research projects from ideation to completion, including managing technical roadmaps and experimental workflows.
• Experience in Python and deep learning frameworks (e.g., JAX, PyTorch, TensorFlow).
• Experience with peer-reviewed publications as lead or primary author in AI/ML venues (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, Nature, Science).

Preferred qualifications:

• Experience as a subject-matter expert in a core subfield of AI, such as large foundation models, reinforcement learning, reasoning, agentic systems, or scientific AI applications.
• Experience bridging the gap between theoretical research breakthrough and large-scale practical product or platform integration.
• Ability to communicate complex scientific concepts effectively to executive leadership, technical partners, and non-specialist audiences.
• Track record of collaborative research environments and driving cross-organization initiatives.

Application Instructions

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