Research Scientist, Multiagent Systems For Social Impact

Snapshot

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

About Us

We are seeking a highly motivated and innovative Research Scientist to join our team in Bengaluru, focused on advancing the state-of-the-art in multiagent systems for social impact. You will conduct cutting-edge research on multiagent systems, including agents based on large language models (LLMs), focusing on acceleration of social impact. This role offers a unique opportunity to contribute to fundamental research in AI while collaborating with a world-class team at Google DeepMind and seeing your work translated into real-world applications. If you are passionate about shaping the future of social impact through AI and are eager to make a significant impact in the rapidly evolving landscape of multiagent systems and AI agents, we encourage you to apply.

• The Role
• As a Research Scientist at Google DeepMind, you will:
• Key responsibilities:

• Conduct cutting-edge research: Develop novel algorithms, models, and techniques for multiagent systems, pushing the boundaries of AI research in areas such as multiagent reinforcement learning, bandit algorithms, diffusion models. Your research will directly contribute to advancing Google’s multiagent capabilities with a particular focus on social impact.
• Develop and evaluate models: Design, implement, and evaluate use of AI agents for social impact. Explore techniques like prompt engineering, few-shot learning, post-training techniques to improve model performance and robustness in diverse real-world scenarios. Your research will be focused on building multiagent systems that can reason, plan, and perform meta-level reasoning to build systems for social impact.
• Collaborate with a world-class team: Work closely with other research scientists, engineers, and product teams across Google DeepMind, fostering a collaborative and intellectually stimulating environment. Share your research findings through publications in top-tier conferences and journals, while also contributing to the development of impactful products.
• Contribute to real-world impact: See your research contribute to real-world social impact with applications across various domains, including healthcare, conservation, and more, potentially influencing future Google products and services.
• Stay at the forefront of AI research: Continuously explore emerging trends and new research directions in multiagent systems and AI agents. Participate in international conferences and workshops to share your work and learn from others in the field.

You are a passionate and talented researcher with a strong theoretical foundation and a proven ability to conduct impactful research in AI. You have a collaborative mindset and are excited to work as part of a team to tackle ambitious research challenges. You are passionate about seeing your research translated into real-world impact that improves lives and are eager to work in an environment where research has a direct path to impact. You are eager to see your research contribute to real-world applications and are driven by a desire to create positive change through AI.

• Ph.D. in Computer Science, Artificial Intelligence, or a related field.
• Strong publication record in top-tier machine learning conferences or journals.
• Solid understanding of multiagent systems research in topics such as multiagent reinforcement learning, game theory, social choice, bandit algorithms.
• Experience with relevant ML frameworks such as JAX, TensorFlow, or PyTorch.

In addition, the following would be an advantage:

• Experience with large language models, and/or AI agents.
• Familiarity with large-scale model training and deployment.
• Strong programming skills in Python or similar languages.
• Excellent communication and collaboration skills.