Research Scientist, Generative AI & Multimodal Systems

Google; Zürich; Hybrid; CHF 180.000 - 250.000; Vollzeit

Zusammenfassung

Google DeepMind seeks a Research Scientist to design and deploy large-scale generative models across multi-modal domains, pushing the boundaries of machine learning research. You will lead experiments, prototype implementations, and apply the latest theories to develop new architectures and scalable products.

You will also publish findings and collaborate with partner universities and institutes worldwide, balancing long-term scientific goals with practical product impact, while upholding safety

Qualifikationen

• PhD degree in computer science, mathematics, applied statistics, machine learning or equivalent practical experience.
• Experience with training generative models (Large Language Model (LLM), image, video).
• Experience of TensorFlow or ML frameworks (e.g. JAX or PyTorch).
• Experience conducting research.
• Publication record in AI conferences (e.g., NeurIPS, CVPR, ICCV, ICLR).

Aufgaben

• Optimize model architectures and training pipelines for distributed training, maximizing compute efficiency across accelerator clusters (TPUs/GPUs).
• Design and train state-of-the-art generative models across multi-modal domains (image, video, and audio).
• Develop and deploy reinforcement learning algorithms to align model behaviors and improve reasoning capabilities.
• Drive efficient inference strategies to minimize latency and memory footprint in production.
• Bridge research and production by translating breakthroughs into scalable algorithms and benchmarks.

Kenntnisse

GenAI model training

Research experience

AI publications

Ausbildung

PhD in CS/ML or equivalent

Tools

TensorFlow

JAX

PyTorch

Jobbeschreibung

Google DeepMind seeks a Research Scientist to design and deploy large-scale generative models across multi-modal domains, pushing the boundaries of machine learning research. You will lead experiments, prototype implementations, and apply the latest theories to develop new architectures and scalable products.

You will also publish findings and collaborate with partner universities and institutes worldwide, balancing long-term scientific goals with practical product impact, while upholding safety