Group Product Manager, Relevance, GeminiApp, DeepMind

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

Job summary

Google DeepMind is seeking a Product Manager for the Gemini Relevance Platform to define and execute the product strategy powering discovery, personalization, and proactive engagement for hundreds of millions of users. You will lead a team of ML engineers and data scientists to transform Gemini into a daily habit across in-app and proactive notifications.

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

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 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 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.

Skills

Product management

0-to-1 recommendations

ML personalization platforms

Feed/discovery ranking

Education

Bachelor’s degree in Computer Science

Tools

Deep ML architectures

Feature store infrastructure

Offline/online training workflows

Low-latency real-time serving

Job description

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.

Minimum 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.

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. 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

Responsibilities

Learn more about benefits at Google .

• 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 workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .