Join Google DeepMind's Agents team in Bengaluru, pioneering advancements in Large Models to achieve Artificial General Intelligence (AGI). Our mission involves exploring emergent agentic behaviors through sophisticated reinforcement learning algorithms at scale.

We contribute research innovations to Gemini and crucial Google product launches, impacting millions of users globally. This role offers a unique opportunity to drive progress in autonomous agents using cutting-edge reinforcement learning and ML optimization techniques.

Google DeepMind is at the forefront of AI development, leveraging interdisciplinary teams to tackle complex global challenges and enhance product innovation. We are committed to using AI for public benefit and scientific discovery, with an unwavering focus on safety and ethics.

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

Advance the frontiers of reinforcement learning and ML optimization methodologies to construct highly capable autonomous agents.

Communicate research findings and project developments clearly and effectively, both internally and externally, through presentations and written reports.

Foster collaborative relationships within the team and with external research laboratories.

Collaborate with Responsible AI teams to ensure ethical development of AI advancements and maximize their societal benefits.

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

Possess at least 8 years of hands-on experience with machine learning frameworks such as JAX, TensorFlow, or PyTorch.

Demonstrated expertise in advanced deep learning and reinforcement learning techniques.

Proven track record of publications in top-tier machine learning conferences or journals (e.g., NeurIPS, ICML, ICLR, KDD, AAAI).

Preferred qualifications include experience with multimodal learning, large language models, or assistive AI agents, alongside familiarity with prompt engineering, few-shot learning, and model evaluation techniques. Strong programming proficiency in Python or similar languages and excellent communication and collaboration skills are essential.