Head of Recommendations & Discovery, ML-Driven

Socket.dev; San Francisco (CA); On-site; USD 177,000 - 256,000; Full time

Benefits offered by this job

Scribd Flex

Health benefits

Paid time off

Job summary

Scribd, Inc. in San Francisco is seeking a Lead Product Manager for the Recommendations domain.

You will own the recommendations experience for 200M+ monthly visitors across a corpus of 300M documents, working at the intersection of ML and product to surface content to the right user at the right time. Success means defining a compelling vision, crafting impactful metrics, and running experiments to deliver breakthrough features.

Qualifications

• 8+ years of product management experience, including in high-traffic consumer environments.
• Proven track record shipping ML-driven features that move core metrics.
• Deep familiarity with retrieval, ranking, embeddings, and feature stores.

Responsibilities

• Define long-term recommendations strategy and multi-year roadmap across candidate generation, ranking, and results presentation.
• Partner with ML Engineering, Applied Research, and data teams to productionize advanced retrieval and ranking.
• Define key metrics and monitor engagement, CTR, content completion, and subscription retention.
• Balance short-term wins with a scalable, extensible recommendations platform aligned with the company AI strategy.
• Synthesize experiments and user feedback to guide prioritization and design.
• Communicate requirements and timelines clearly to stakeholders across functions.

Skills

PM experience

ML features

Cross-functional leadership

Data-driven decisions

Education

Bachelor's degree in CS/Engineering

Tools

SQL

A/B testing

ML tooling

Job description

Scribd, Inc. in San Francisco is seeking a Lead Product Manager for the Recommendations domain.

You will own the recommendations experience for 200M+ monthly visitors across a corpus of 300M documents, working at the intersection of ML and product to surface content to the right user at the right time. Success means defining a compelling vision, crafting impactful metrics, and running experiments to deliver breakthrough features.