Research Scientist

About The Job

Google DeepMind is a pioneering AI lab with interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are a priority.

Key Responsibilities

• Generate new ideas and keep up with the state-of-the-art in the field.
• Discuss research directions with other researchers.
• Design, rapidly implement, and evaluate ideas, methods, interfaces, and tools to explore new sociotechnical AI systems.
• Report and present research findings and developments clearly and efficiently, both internally and externally.
• Suggest and engage in inter and intra-team collaborations to meet research goals, while driving significant individual contributions.
• Take ownership of substantial technical projects from ideation to evaluation, often involving cross-functional collaboration.
• Setup large-scale tests and deploy promising ideas quickly.
• Manage deadlines and deliverables while applying the latest theories to develop new products, processes, or technologies.
• Contribute to the wider research community by sharing and publishing findings.

Requirements & Tech Stack

• Python
• Deep learning frameworks: JAX, Flax, or Gemma
• Multimodal AI models and systems
• Research and development: experimental design, implementation, and analysis
• Publication record in machine learning conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, ECCV)

Qualifications

• PhD degree in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
• Experience in fine-tuning and post-training LLMs using Reinforcement Learning (RL) or other alignment methods.
• Experience with developing generative AI architectures, techniques, and agentic AI solutions.
• Experience with multimodal learning, integrating information from different data types (e.g., vision, audio, text).
• Proven expertise in working with, tuning, and prototyping large-scale vision-language models (VLMs) using modern prompting strategies.
• Strong interest in and awareness of the AI alignment, safety, responsibility, and fairness landscape.