Staff Research Engineer, GenAI Reinforcement Learning, DeepMind

As a Research Engineer/Scientist working on Reinforcement Learning (RL) in Gen AI, you will be on the critical path of further improving our foundational models into more helpful and powerful AI agents through reinforcement learning. This is a unique opportunity that has a direct and profound impact on the utility and safety of one the world's most advanced AI systems.

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 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Develop innovative post-training or RL solutions to advance the capability of our Gemini models.
• Develop, maintain, and improve the core RL libraries, tools, and frameworks to accelerate and scale the RL development.
• Collaborate with partners across DeepMind and Google to apply the model in critical product areas.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, and launching software products.
• 3 years of experience with software design and architecture.
• Experience with reinforcement learning, machine learning, and deep learning.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 8 years of experience with data structures and algorithms.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• Experience in developing reinforcement learning algorithms, framework or infrastructure.