Research Scientist, Recursive Self Improvement and Post Training, DeepMind

In this role, you will join a team of research scientists working on humanity's critical path to AGI. You will focus on reasoning, post training and recursive self improvement to not only improve Gemini but also drive significant breakthroughs for science and humanity, an incredible opportunity to work at the frontier of AI from Singapore.

As a part of the Gemini core team, you will work on recursive self improvement, post-training, frontier-level math/code and push the bleeding edge of AI. As a part of this team, you will work closely with the Gemini core teams, alongside incredible talent density, positioned to make a significant impact on Google, science and humanity in general.

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.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Responsibilities

• Conduct critical research in recursive self improvement and post-training

• Anticipate where the next game changers will come from, staying mindful of upcoming research breakthroughs, and build research agendas based on new paradigms to execute on them.

• Execute on promising research agendas by working as a team.

• Collaborate with other Gemini core teams, mostly based in the US and UK.

Minimum qualifications:

• PhD in Computer Science, Artificial Intelligence, Robotics, Mathematics, Physics, Computational Biology, or a related STEM field, or equivalent practical research experience.

• 3 years of experience initiating, scoping, and executing independent research agendas or leading academic projects.

• Experience conducting research in Reinforcement Learning (RL), reasoning or agentic coding.

• Experience with research projects in Large Language Models (LLM).

• One or more peer-reviewed scientific publication submissions (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, CoRL) or public preprint repositories (arXiv).

Preferred qualifications:

• 2 years of experience in coding and leading multiple research efforts and influencing research direction.

• Experience driving research projects from conception to completion.

• Experience in LLM related infrastructure, or engineering.

• Ability to work in a fast-paced, dynamic, and collaborative environment.

• A track record of research or engineering achievements, including publications in peer-reviewed conferences or journals.

• Excellent problem-solving, investigative, and communication skills.