Join DeepMind India's Agents team, at the forefront of developing foundational capabilities in Large Models to advance Artificial General Intelligence (AGI). We are dedicated to discovering emergent agentic behaviors through innovative reinforcement learning algorithms at scale. Our research directly influences Gemini and critical Google product launches, impacting hundreds of millions of users worldwide.

We are actively seeking a highly motivated Research Scientist to enhance our work on autonomous agents using reinforcement learning and ML optimization methods. This role is crucial for driving advancements in large language models (LLMs), focusing on creating more capable autonomous agents. You will lead efforts in designing novel algorithmic architectures, with the ultimate goal of solving and building Artificial General Intelligence. Collaboration across research fields will be key to tackling fundamental questions in machine learning and AI.

Google DeepMind is a leading AI laboratory committed to using transformative AI technologies to address complex global challenges and accelerate high-quality product innovation for billions. Our work prioritizes widespread public benefit, scientific discovery, and unwavering commitment to safety and ethics. We offer diverse learning opportunities and career paths for individuals driven to achieve exceptional results through collective effort.

Design, implement, and rigorously evaluate models, agents, and software prototypes for large foundational models.

Advance the frontiers of reinforcement learning and ML optimization techniques to engineer sophisticated autonomous agents.

Clearly and efficiently communicate research findings, developments, status, and results through both written and verbal presentations, both internally and externally.

Propose and actively participate in collaborative initiatives, both within the team and with external research laboratories, fostering strong relationships.

Partner closely with our Responsible AI teams to ensure that advancements in intelligence are developed ethically and contribute broadly to human well-being.

A PhD degree in Computer Science, Artificial Intelligence, or a related discipline, or equivalent practical experience, is essential.

Demonstrated expertise with a minimum of 8 years of hands-on experience utilizing machine learning frameworks such as JAX, TensorFlow, or PyTorch.

Proven experience in advanced deep learning and reinforcement learning methodologies.

A strong publication record in reputable machine learning conferences or journals, including but not limited to NeurIPS, ICML, ICLR, KDD, and AAAI.

Preferred qualifications include experience with multimodal learning, large language models, or assistive AI agents. Familiarity with prompt engineering, few-shot learning, post-training techniques, and evaluations is advantageous. Proficiency in model training and deployment, coupled with strong programming skills in Python or similar languages, is highly valued. Excellent communication and collaboration skills are fundamental for success in this role.