Senior Product Lead - ML-Driven Recommendations

Scribd, Inc.; Los Angeles (CA); On-site; USD 177,000 - 256,000; Full time

Benefits offered by this job

Scribd Flex (flexible work model)

Comprehensive health coverage

Generous paid time off

Employee equity

Learning and development programs

Wellness & home office stipends

Access to Scribd suite of products

Job summary

Scribd, Inc. in San Francisco seeks a Lead Product Manager, Recommendations, to own the recommendations experience for 200 million monthly visitors across a corpus of 300 million documents.

You'll work at the intersection of ML and product to surface the right content to the right person at the right time, defining vision, metrics, and breakthrough features with Engineering, Analytics, Data Science, Design, and ML teams.

Qualifications

• 8+ years of product management experience in a high-traffic consumer environment.
• 4+ years leading recommendations or search products.
• ML-driven features that moved core business metrics at scale.
• Familiarity with retrieval and ranking algorithms and embeddings.
• Ability to shape long-term vision and align cross-functional teams.
• Excellent written and verbal communication for senior leadership.

Responsibilities

• Chart the long-term recommendations strategy and multi-year roadmap.
• Partner with ML Engineering & Applied Research to productionize research.
• Define metrics that matter: engagement, click-through, conversions.
• Balance short-term wins with a scalable, extensible platform.
• Fuse data with customer feedback to inform prioritization and design.
• Communicate requirements and timelines clearly to stakeholders.

Skills

Product management

ML-driven features

Cross-functional collaboration

Data-driven decisions

Communication skills

User journey thinking

Education

Bachelor's degree in CS/Engineering/Math

Job description

Scribd, Inc. in San Francisco seeks a Lead Product Manager, Recommendations, to own the recommendations experience for 200 million monthly visitors across a corpus of 300 million documents.

You'll work at the intersection of ML and product to surface the right content to the right person at the right time, defining vision, metrics, and breakthrough features with Engineering, Analytics, Data Science, Design, and ML teams.