Product Manager, Math Agents, DeepMind (Fixed Term Contract)

Google · London, UK

As a Product Manager on the Science team, you will work directly with research scientists, engineers, and cross-functional product development teams to define the product strategy, goal, and execution for our math agents portfolio. In this role, you will play a critical role in building and scaling these agentic systems, bridging frontier research in automated reasoning and autonomous mathematical exploration with real-world mathematical issues.

You will lead the development and deployment these systems, while also steering grand issues and research efforts across the broader maths space. You will sit at the intersection of research and product, and requires technical depth, strategic insight, an ability to navigate ambiguity, and an approach to prototyping and validation.

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.

Minimum qualifications:

  • Bachelor's degree in Mathematics, Computer Science, or a related quantitative field or equivalent practical experience.
  • 5 years of experience in product management or related technical role.
  • Experience with advanced AI/ML concepts, including large language models (LLMs) research and products.

Preferred qualifications:

  • Experience with and passion for mathematics, e.g. an advanced degree in math or related fields.
  • Experience with products geared toward a highly technical user base.
  • Familiarity with formal proof systems, e.g. Lean, SageMath.
  • Ability to think creatively about the applications, risks, and benefits of new technologies in technical domains.
  • Ability to foster collaboration and bring people together across different research initiatives and product teams.
  • Excellent technical fluency, with the ability to engage with research scientists and engineers on model capabilities, limitations, and agent architectures.
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