Group Product Manager, Relevance & Personalization GeminiApp

Google LLC; 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

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,