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Open nowFirst seen 8 hours ago

Product Manager, Computer Use, DeepMind

Google DeepMind157 open roles

Where
Mountain View, CA, USA
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Your applicationOpen nowProduct Manager, Computer Use, DeepMindGoogle DeepMind · Mountain View, CA, USA

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Google DeepMind's own form.

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The clock on this job

Early applications get read.

13.5% of postings close within 7 days. Measured by our own scanner across the market. Google DeepMind postings stay open a median of 26 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.6%3 days
  3. 13.5%7 days
  4. 21.8%14 days
  5. 36.6%30 days
  6. 58.9%60 days
This job: first seen 8 hours ago

Google DeepMind median: 26 days open

The posting

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 5 years of experience in product management, particularly foundation models, multimodal agents, computer use, or browser/UI automation.

Preferred qualifications:

  • Experience shipping AI capabilities into consumer or enterprise products (e.g., browsers, operating systems, productivity tools) as well as developer APIs and cloud platforms.
  • Track record of defining evaluation frameworks, real-world benchmarks, and quality metrics for AI systems, translating complex enterprise or developer workflows into model requirements.
  • Ability to navigate model capability and serving tradeoffs across quality, latency, and cost (e.g., model routing, post-training, and agent harnesses).
  • Excellent strategic thinker with a bias for action.

About the job

In this role, you'll join the Gemini model Product Management team at Google DeepMind, which shapes what the core Gemini model can do: setting capability priorities, defining quality bars and evals with research, and landing each Gemini release across Google products and developer platforms. Within it, you'll be part of the multimodal team, which unlocks multimodal agents that can see, understand, and act across first-party and third-party surfaces.

Computer use is one of the biggest opportunities for those agents. Much of what people do every day, at work and at home, happens in software built for humans, not agents: SaaS apps, legacy systems, portals, and consumer websites and apps that will never have an API. Making Gemini the best engine for computer use agents lets it finish the job when an API is missing.

You'll partner with the pre-training and post-training research teams that own computer use, and bring it to hero surfaces like Gemini in Chrome, the Gemini API, Gemini Enterprise, and Android.

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.

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

US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Define the product strategy and roadmap for computer use. Engage with enterprise customers, developers, and the broader agent ecosystem to synthesize user feedback, uncover capability gaps, and bring back market and competitive signals to inform that outlook.
  • Own the quality bar for computer use capabilities and build out dedicated, real-world evals. Identify high-value workflows, define new eval slices, and drive the data and post-training strategy required to reach production-grade reliability.
  • Bring this outlook to life across Google's products and developer platforms. Partner with teams across Google to define launch criteria and ship computer use experiences in products like Chrome, while driving developer and enterprise adoption through the Gemini API and Google Cloud.
  • Influence technical roadmaps and model tradeoffs.
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