Product Manager, Math Agents, Deepmind (fixed Term Contract)

Google Google · Big Tech · London, United Kingdom

Product Manager for AI math agents at Google DeepMind, focusing on defining product strategy, requirements, and execution for agentic systems that bridge frontier research in automated reasoning with real-world mathematical problems. The role involves leading development and deployment, incubating new agentic capabilities, and collaborating with researchers and mathematicians.

What you'd actually do

  1. Drive the product strategy, requirements, and execution for the math agents portfolio, guiding initiatives across agentic maths research and formal proving like AI co-mathematician, AlphaProof, AlphaProof Nexus, and more.
  2. Incubate new agentic capabilities and identify nascent research to create transformative tools for the scientific and mathematical communities.
  3. Advocate and represent the mathematician, building deep familiarity with their workflows, needs, and pain points to design intuitive research interfaces.
  4. Lead the early access program and trusted tester initiatives, collaborating directly with academic mathematicians and researchers to validate our tools on high-impact conjectures and papers.
  5. Flex to other strategic initiatives in Science as needed.

Skills

Required

  • Product management experience
  • Experience with advanced AI/ML concepts
  • Experience with large language models (LLMs) research and products
  • Bachelor's degree in Mathematics, Computer Science, or a related quantitative field or equivalent practical experience

Nice to have

  • Experience with and passion for mathematics
  • 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

What the JD emphasized

  • building and scaling these agentic systems
  • bridging frontier research in automated reasoning and autonomous mathematical exploration
  • agentic maths research
  • agentic capabilities
  • Experience with advanced AI/ML concepts, including large language models (LLMs) research and products
  • technical fluency

Other signals

  • building and scaling these agentic systems
  • bridging frontier research in automated reasoning and autonomous mathematical exploration
  • Drive the product strategy, requirements, and execution for the math agents portfolio
  • Incubate new agentic capabilities
  • Experience with advanced AI/ML concepts, including large language models (LLMs) research and products