Lead Product Manager, Search

Qualifications

• 6+ years of product management experience, including 4+ years leading search or recommendations products in a high-traffic consumer environment
• Demonstrated success shipping ML-driven features that moved core business metrics (engagement, conversion, or revenue) for large scale products
• Experience designing LLM- and GenAI-enhanced user experiences that go beyond raw chat to deliver task-specific value
• Hands-on proficiency with SQL and a scripting language (Python or R) for rapid data exploration
• Proficiency with prototyping tools, and model evaluation
• Deep familiarity with retrieval and ranking algorithms, embeddings, and feature stores
• Track record of thriving amid ambiguity: shaping a multi-year vision, aligning cross-functional teams, and delivering incremental wins along the way
• Exceptional written and verbal communication skills — adept at crafting product briefs, bringing in inputs from multiple teams, and presenting data-backed decisions to senior leadership
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience)
• Bonus points: Familiarity with modern ML operations tooling — from vector databases to end-to-end model-ops workflows (MLOps / LLMOps) — and the ability to collaborate with engineering teams that rely on these systems

Responsibilities

• Chart the long-term search strategy — own a multi-year roadmap spanning query understanding, retrieval, ranking, and results presentation across Scribd's surfaces, guiding every user from intent to the right document
• Partner with ML Engineering & Applied Research — translate cutting-edge retrieval and ranking research into production systems that blend semantic embeddings, BM25, and real-time behavioral signals for best-in-class relevance
• Define the metrics that matter — establish and monitor leading indicators of search success: query success rate, zero-result rate, click-through, and downstream subscription conversion and retention
• Balance short-term wins with long-term vision — ship incremental relevance improvements that hit revenue goals while building an extensible search platform aligned with Scribd's 3-year AI strategy
• Fuse data with the voice of the customer — synthesize experiment results, query analytics, user interviews, and feedback sessions to inform prioritization and feature design
• Communicate with clarity and influence — align product, engineering, design, content, and executive stakeholders by clearly articulating requirements, timelines, deliverables, and expected impact, securing buy-in at every stage