Scribd
Lead Product Manager, Recommendations
San Francisco · Senior · Contract
Sponsorship not specifiedDetected 86 days ago
AlgorithmsSQLMachine LearningData ScienceLLMsMLOpsProduct ManagementResearchLeadershipCommunicationCollaborationPublic Speaking
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odds of building a lasting career here
40Risky
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
Lottery odds assume a STEM candidate.
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About the role
- Our four products - Scribd®, Slideshare®, Everand™, and Fable - help billions of people across the globe move beyond access and into insight, application, and expertise.
- So what are we looking for in new team members?
- At Scribd, Inc., we hire for "GRIT." Traditionally defined as the intersection of passion and perseverance toward long-term goals, GRIT reflects the mindset we expect from every employee.
Responsibilities
- Chart the long-term recommendations strategy - own a multi-year roadmap spanning candidate generation, ranking, and results presentation across Scribd's surfaces, guiding every user from interest to the right document
- Partner with ML Engineering & Applied Research - translate cutting-edge retrieval and ranking research into production systems that blend collaborative signals, content embeddings, and real-time behavioral data for best-in-class personalization
- Fuse data with the voice of the customer - synthesize experiment results, behavioral analytics, user interviews, and feedback 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
- We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas.
- Come join us in building something meaningful.
Requirements
- 8+ years of product management experience, including 4+ years leading recommendations or search products in a high-traffic consumer environment
- Deep familiarity with retrieval and ranking algorithms, embeddings, and feature stores - paired with the ability to reason about end-to-end customer journeys for distinct user segments
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience)
- Familiarity with modern ML ops tooling
- Demonstrated success shipping ML-driven features that moved core business metrics (engagement, conversion, or revenue) at scale
- Exceptional written and verbal communication skills - adept at crafting product briefs and presenting data-backed decisions to senior leadership
- Hands-on proficiency with AI tools for productivity and analytics - including LLM-powered workflows, SQL copilots, and data exploration tools - to move fast, prototype ideas, and pressure-test assumptions without always needing engineering support
- Experience designing LLM- and GenAI-enhanced discovery experiences that go beyond raw recommendations to deliver personalized, task-specific value
Compensation
- At Scribd, Inc., your base pay is one part of your total compensation package and is determined within a range.
Benefits
- Comprehensive health, dental, and vision coverage
- Mental health support and disability coverage
- Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals
- Paid parental leave and family support benefits
- Retirement matching and employee equity
- Learning and development programs and professional growth opportunities
- Wellness and home office stipends
- Balance short-term wins with long-term vision - ship incremental relevance improvements that hit revenue goals while building an extensible recommendations platform aligned with Scribd, Inc.'s 3-year AI strategy
- Track record of thriving amid ambiguity: shaping a multi-year vision, aligning cross-functional teams, and delivering incremental wins along the way
- Scribd Flex (flexible work model)
This listing is sourced directly from Scribd's careers page and normalized into a canonical job model.