Research Scientist, Gemini Retrieval and Agera, DeepMind

About the Job

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $301000 (USD) + 20% bonus target + bonus + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Design modeling innovations to enable Gemini to autonomously acquire and reason over deep, structured domain knowledge.
• Advance next-generation retrieval architectures and natively multimodal Gemini representations to improve intent capture and retrieval quality.
• Build and train models that can autonomously reflect on outputs and self-improve through experience.
• Collaborate with product teams like Search and YouTube to scale research innovations into production environments, optimizing for both quality and efficiency.

Qualifications

Minimum qualifications:

• Bachelor's degree in Computer Science, a relevant technical field with a focus on AI research, or equivalent practical experience.
• 8 years of experience in the full lifecycle of research modeling, with a specific emphasis on ensuring quality outputs and autonomous learning in AI domains.
• Experience in the full lifecycle of research modeling, with a specific emphasis on ensuring quality outputs and autonomous learning in AI domains.
• Experience in developing and scaling Large Language Models (LLMs) or Information Retrieval (IR) systems.

Preferred qualifications:

• Knowledge of Reinforcement Learning (RL) or automated evaluation systems.
• Ability to solve exceptionally complex problems (e.g., math and programming competitions or developing novel algorithms).
• Ability to quickly prototype and iterate on complex systems.
• Strong coding skills and a "hacker" mindset for implementing complex algorithms and multi-stage training pipelines.
• Interest in the intersection of research and large-scale real-world applications.