Group Product Manager, Architectural Advances, Frontier AI, DeepMind

On-site in London·Added 6 days ago (last checked 22 Oct)

Google

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Overview

Work mode: On-site, London
Experience: 10+ years

Skills

Requirements

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.

The role

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. Note: By applying to this position you will have an opportunity to share your preferred working location from the following: London, UK; Mountain View, CA, USA.

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.

Hiring process

4 steps3 interviewsa task to do6–8 weeks in all

Apply online
Assessments
Online test · Not every role
You may be asked to take the Google Hiring Assessment (workstyle skills) and, for some roles, role-related assessments such as a coding exercise.
Recruiter conversations
With a recruiter · Phone call · 1–2 sessions
One or two shorter conversations assessing key skills, sharing information about the organisation and team, and asking about your preferences such as location.
Project work
In your own time · Not every role
For some roles, a small project before interviews: a case study, writing or code samples.
Interviews
With a rotating cast of Googlers
A panel of structured interviews, over video or in person, with a rotating cast of Googlers; open-ended role-related questions scored against the same rubric for every candidate, no brainteasers.
Decision and offer · With a recruiter

Structured interviews: every candidate for a role is scored against the same rubric; no brainteasers.
AI tools are not permitted during interviews.
For some roles, pre-selected interviews happen virtually before final interviews onsite.