Product Manager, Computer Use, DeepMind

Google•Mountain View, CA

11h•$163,000 - $236,000

About The Position

The Product Manager will join Google DeepMind’s Gemini model Product Management team, which sets capability priorities, defines quality standards and evaluations with research teams, and brings Gemini releases to Google products and developer platforms. As part of the multimodal team, this role will help develop agents that can see, understand, and act across first-party and third-party surfaces. The role focuses on computer-use capabilities that enable Gemini agents to complete tasks in software built for people, including SaaS applications, legacy systems, portals, and consumer websites and apps without APIs. The Product Manager will partner with pre-training and post-training research teams and help bring computer use to products and platforms such as Gemini in Chrome, the Gemini API, Gemini Enterprise, and Android. Individual pay is determined by job-related skills, experience, and relevant education or training. The stated US compensation range is $163,000–$236,000, plus a 15% bonus target, equity, and benefits.

Requirements

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

Nice To Haves

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

Responsibilities

Define the product strategy and roadmap for computer use, synthesizing feedback and market and competitive signals from enterprise customers, developers, and the broader agent ecosystem.
Own the quality bar for computer-use capabilities and develop real-world evaluations; identify high-value workflows, define evaluation slices, and drive the data and post-training strategy needed for production-grade reliability.
Partner with teams across Google to define launch criteria and ship computer-use experiences in products such as Chrome, while driving developer and enterprise adoption through the Gemini API and Google Cloud.
Influence technical roadmaps and model tradeoffs.