Frontier AI Research Scientist — Multimodal & LLMs Leader

Google; Lavamünd; Vor Ort; EUR 130.000 - 165.000; Vollzeit

Zusammenfassung

Google DeepMind’s Frontier AI unit invites applications for a Research Scientist to advance foundational AI architectures and frontier models. You will collaborate with researchers and engineers globally to construct AI models capable of cross-modal reasoning and scalable learning.

As part of a high-impact team, you will push the boundaries of AI safety and ethics while shaping research strategies, benchmarks, and high-quality publications that drive real-world scientific and societal benefits.

Qualifikationen

• PhD in ML/CS/Statistics or equivalent practical experience.
• 15 years of experience leading a research agenda.
• Expertise in deep learning, Python and neural network training.
• Experience training, evaluating and interpreting large multimodal models and large language models.
• Publication record in ML conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, ECCV).

Aufgaben

• Define and lead ambitious research projects, setting technical direction and ensuring successful execution of the research agenda.
• Design and implement innovative model architectures that learn from diverse modalities and datasets.
• Develop benchmarks for evaluating frontier AI systems across capabilities and domains.
• Contribute to the team research strategy and influence the broader community through publications and talks.

Kenntnisse

Deep learning

Python

Neural network training

Multimodal models

LLMs

Ausbildung

PhD in ML/CS/Statistics

Jobbeschreibung

Google DeepMind’s Frontier AI unit invites applications for a Research Scientist to advance foundational AI architectures and frontier models. You will collaborate with researchers and engineers globally to construct AI models capable of cross-modal reasoning and scalable learning.

As part of a high-impact team, you will push the boundaries of AI safety and ethics while shaping research strategies, benchmarks, and high-quality publications that drive real-world scientific and societal benefits.