{"id":3394524,"url":"https://alion.io/job/google-deepmind-group-product-manager-relevance-geminiapp","title":"Group Product Manager, Relevance, GeminiApp","company":{"id":4,"name":"Google DeepMind","domain":"deepmind.google","url":"https://alion.io/company/deepmind","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":null},"role":"Product","role_family":"Product","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mountain View, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":200000,"max_usd":370000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":712},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Embeddings","optional":false},{"name":"Gemini","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Machine Learning","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Feature Store","optional":true}],"status":"live","first_seen_at":"2026-10-28T08:10:09Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-11-05T03:19:21Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"About the job\nAs 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.\nIn 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.\nArtificial 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.\nIndividual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $240000 - $333000 (USD) + 25% bonus target + equity + benefits\nLearn more about benefits at Google.\nResponsibilities\nDefine the multi-quarter strategy and roadmap to evolve Gemini’s recommendation engine from rules-based ranking into sophisticated deep ranking and retrieval models.\nLead product development for zero-state prompt discovery, contextual suggestions, session resume modules (\"Pick Up Where You Left Off\"), and proactive daily routines.\nPartner with Growth and Notification Platform teams to build ML-driven targeting, personalized delivery windows, and lifecycle campaigns that drive incremental daily active users (DAU).\nCollaborate with cross-Google teams (Search, YouTube, Workspace) to safely and privacy-compliantly leverage rich ecosystem signals, knowledge graph entities, and semantic embeddings.\nEstablish the metrics hierarchy balancing short-term click engagement (CTR) with downstream conversation depth, response quality, and long-term user persistence.\nQualifications\nMinimum qualifications:\nBachelor's degree in Computer Science or equivalent practical experience.\n10 years of experience in product management or a related role.\nExperience as a Product Manager managing 0-to-1 recommendation systems, ML personalization platforms, or feed/discovery ranking products.\nPreferred qualifications:\nDeep technical fluency with modern ML architectures, feature store infrastructure, offline/online training workflows, and low-latency real-time serving constraints.\nExceptional cross-functional leadership skills across Engineering, Data Science, UX, Legal/Privacy, and partner product organizations.\nProven track record driving core growth and engagement metrics (DAU, CTR, session 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