About this role
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
Learn more about benefits at Google (https://www.google.com/about/careers/applications/benefits/).
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.
- 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.