Research Scientist, Multimodal Alignment, Safety and Fairness

Highlights

• Advance multimodal alignment, safety and fairness at Google DeepMind.
• Design and evaluate new sociotechnical AI systems for global impact.
• Publish findings and collaborate across disciplines and universities.

What they offer

• 15% bonus target
• equity
• benefits

Ideal candidate

PhD-level multimodal researcher passionate about AI alignment, safety and fairness who thrives prototyping large-scale ideas and sharing findings openly across disciplines.

Requirements

• PhD in Computer Science, Machine Learning or related technical field or equivalent practical experience
• Experience in Python and deep learning frameworks (e.g., JAX, Flax, or Gemma)
• Experience developing multimodal AI models and systems
• Experience conducting research and development including experimental design, implementation and analysis
• Publication record in machine learning conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, ECCV)
• Experience fine-tuning and post-training LLMs using Reinforcement Learning or other alignment methods
• Experience developing generative AI architectures, techniques and agentic AI solutions
• Experience with multimodal learning integrating vision, audio and text
• Expertise working with, tuning and prototyping large-scale vision-language models using modern prompting strategies
• Interest in AI alignment, safety, responsibility and fairness with excitement to collaborate across disciplines