Google

Group Product Manager, Architectural Advances, Frontier AI, DeepMind

Google London, England, United Kingdom · $240K–$333K/yr

Software Development · 10,001+ employees

Oct 16
product-manager Principal (10+ yrs) Full-time United Kingdom
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About the role

You will lead the integration of AI research breakthroughs into Google's models and products while collaborating with researchers and product teams. Responsibilities include defining strategy for model architecture adoption and deploying new model families across various product areas.

What they look for

AI Product Management AI Architecture Model Development Strategic Planning Technical Communication Stakeholder Management AGI Research Product Strategy Cross-functional Collaboration Ecosystem Strategy Gemini Robotics Agents

Requirements

Candidates must hold a bachelor's degree in Computer Science or equivalent and possess at least 10 years of experience in building AI products. Strong technical communication skills and the ability to navigate complex, high-stakes environments are essential.

Benefits

Bonus Equity Health Insurance

Full description

Minimum qualifications:

  • Bachelor's degree in Computer Science or equivalent practical experience.
  • 10 years of experience building AI products, including AI architecture and models.

Preferred qualifications:

  • Understanding of the current model landscape and strengths or weaknesses of various techniques.
  • Ability to stay up-to-speed on all relevant research in core model advancements.
  • Ability to zoom out and predict model gaps which will need to be addressed to get us to AGI.
  • Ability to build clear goals and strategies of how model advancements can be turned into incredible product features.
  • Strong ability to communicate complex technical advancements with great simplicity.
  • Very strong ability to collaborate in high stakes environments with multiple executive stakeholders and technical leads.

About the job:

As a Product Manager at DeepMind, you will be responsible for the shipping AI research breakthroughs into Google’s AI models and products. You will be working with brilliant AI researchers who are focused on making the biggest advances across new model architectures, AGI and advanced applications like Agents and Robotics. You will understand the implications of new architectures on Gemini and other models, help teams navigate the tradeoffs and build collaborations with model development teams, work with various product areas like Cloud and Search to understand customer needs and how model advancements can address those needs. In addition to shipping architectural advances directly into our models, you may sometimes also ship a new model family or work with products to ship custom models directly into products. You will also help research teams build the communication and ecosystem strategy for the model advancements so that they get the right level of adoption and awareness.Artificial intelligence will be one of humanity’s most transformative inventions. At 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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $240000 - $333000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities:

  • Understand implications of new model architecture breakthroughs on Gemini and other models.
  • Build collaborations with product teams and model development teams to ship model architecture advances.
  • Work with Google product areas and understand customer needs which can be met much better with specific model architecture advancements.
  • Build an ecosystem of tooling and infrastructure to enable new model advances to become viable alternatives to existing ones.
  • Deploy entirely new models.

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