Research Scientist, World Models, DeepMind

• Drive research and implementation of new architectures to build frontier generative models with real-time performance.
• Design, evaluate, and generate datasets to discover new model capabilities.
• Collaborate across capability workstreams to discover and scale optimal training recipes.
• Work across the training stack to land new generative and world model capabilities.
• Stay current with the latest research literature and advancements in diffusion models and generative video architectures.

Minimum qualifications:

• PhD in Computer Science, Machine Learning, Statistics, Mathematics, a related technical field, or equivalent practical experience.
• 2 years of experience publishing research in machine learning conferences or releasing open/closed-source software models.
  
• 2 years of experience in diffusion models, multimodal generative models, or generative video models.
  

Preferred qualifications:

• 3 years of experience working in frontier AI research labs on pre-training or post-training teams.
  
• Experience writing TPU/GPU kernels (e.g., JAX, CUDA) to optimize model performance and real-time inference.
  
• Experience designing, training, and scaling generative pixel or real-time video architectures.
• Track record of cross-functional research collaboration delivering models.

• PhD in Computer Science, Machine Learning, Statistics, Mathematics, a related technical field, or equivalent practical experience.
• 2 years of experience publishing research in machine learning conferences or releasing open/closed-source software models.
  
• 2 years of experience in diffusion models, multimodal generative models, or generative video models.