Group Product Manager, Relevance, GeminiApp, DeepMind

Google; Mountain View, San Francisco (CA, CA); On-site; USD 240,000 - 333,000; Full time

Job summary

Google DeepMind’s Gemini Relevance Platform seeks a Group Product Manager to define and execute strategy for the ML engine powering discovery and personalization across Gemini App. You will lead a high-caliber team of ML engineers and data scientists, driving Gemini into a daily habit for hundreds of millions of users worldwide.

You will sit at the intersection of applied ML, systems architecture, and core product UX, owning the roadmap to evolve from heuristic discovery to deeply personalized,

Qualifications

• Bachelor's degree in Computer Science or equivalent practical experience.
• 10 years of experience in product management or a related role.
• Experience as a Product Manager managing 0-to-1 recommendation systems, ML personalization platforms, or feed/discovery ranking products.

Responsibilities

• Define multi-quarter strategy and roadmap for Gemini’s recommendation engine.
• Lead product development for zero-state prompt discovery and proactive daily routines.
• Partner with Growth and Notification Platform teams for ML-driven targeting and lifecycle campaigns.
• Collaborate with cross-Google teams to leverage ecosystem signals and embeddings.
• Establish metrics balancing CTR with long-term user persistence.

Skills

Bachelor's degree requirement

10+ years experience

PM for 0-to-1 systems

Education

Bachelor's degree in Computer Science or equivalent

Job description

Group Product Manager, Relevance, GeminiApp, DeepMind

Share Group Product Manager, Relevance, GeminiApp, DeepMind

corporate_fare DeepMind place Mountain View, CA, USA ; San Francisco, CA, USA ; +1 more

X Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; San Francisco, CA, USA; New York, NY, USA.

• Bachelor's degree in Computer Science or equivalent practical experience.
• 10 years of experience in product management or a related role.
• Experience as a Product Manager managing 0-to-1 recommendation systems, ML personalization platforms, or feed/discovery ranking products.

Preferred qualifications:

• Deep technical fluency with modern ML architectures, feature store infrastructure, offline/online training workflows, and low-latency real-time serving constraints.
• Exceptional cross-functional leadership skills across Engineering, Data Science, UX, Legal/Privacy, and partner product organizations.
• Proven track record driving core growth and engagement metrics (DAU, CTR, session quality) through rigorous A/B experimentation and causal modeling.

About the job

As the Product Manager for Gemini Relevance Platform, you will define and execute the product strategy for the machine learning engine powering discovery, personalization, and proactive engagement across the Gemini App. You will lead a high-caliber team of ML engineers and data scientists tasked with turning Gemini into an indispensable daily habit for hundreds of millions of users worldwide.

In this role, you will sit at the intersection of applied machine learning, systems architecture, and core product UX. You will own the roadmap transitioning Gemini from heuristic, random zero-state discovery into deeply personalized, intent-aware experiences across both in-app entry points and proactive out-of-app notifications.

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.

About the job

As the Product Manager for Gemini Relevance Platform, you will define and execute the product strategy for the machine learning engine powering discovery, personalization, and proactive engagement across the Gemini App. You will lead a high-caliber team of ML engineers and data scientists tasked with turning Gemini into an indispensable daily habit for hundreds of millions of users worldwide.

In this role, you will sit at the intersection of applied machine learning, systems architecture, and core product UX. You will own the roadmap transitioning Gemini from heuristic, random zero-state discovery into deeply personalized, intent-aware experiences across both in-app entry points and proactive out-of-app notifications.

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

• Define the multi-quarter strategy and roadmap to evolve Gemini’s recommendation engine from rules-based ranking into sophisticated deep ranking and retrieval models.
• Lead product development for zero-state prompt discovery, contextual suggestions, session resume modules ("Pick Up Where You Left Off"), and proactive daily routines.
• Partner with Growth and Notification Platform teams to build ML-driven targeting, personalized delivery windows, and lifecycle campaigns that drive incremental daily active users (DAU).
• Collaborate with cross-Google teams (Search, YouTube, Workspace) to safely and privacy-compliantly leverage rich ecosystem signals, knowledge graph entities, and semantic embeddings.
• Establish the metrics hierarchy balancing short-term click engagement (CTR) with downstream conversation depth, response quality, and long-term user persistence.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, is subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.