Senior PM, ML-Powered Discovery & Recommendations

Scribd; Dallas (TX); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Healthcare Insurance Coverage (Medical

12 weeks parental leave

401k matching

Tuition Reimbursement

Sabbaticals

Company-wide events

Wellness stipend

Job summary

Scribd seeks a senior product manager to own the recommendations experience for hundreds of millions of readers. You’ll shape the end-to-end discovery journey, balancing retrieval, ranking, and personalization with a scalable platform vision.

You’ll partner with ML, data science, design and engineering to define metrics, drive multi-year roadmaps, and ship ML-driven features that move engagement and revenue while guiding Scribd’s 3-year AI strategy.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience).
• Exceptional written and verbal communication skills — adept at crafting product briefs and presenting data-backed decisions to senior leadership.
• 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.
• 8+ years of product management experience, including 4+ years leading recommendations or search products in a high-traffic consumer environment.
• Demonstrated success shipping ML-driven features that moved core business metrics (engagement, conversion, or revenue) at scale.
• Track record of thriving amid ambiguity: shaping a multi-year vision, aligning cross-functional teams, and delivering incremental wins along the way.
• 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.
• Familiarity with modern ML ops tooling

Responsibilities

• Own Scribd’s recommendations experience — helping 200 million monthly visitors discover content they didn’t know they were looking for, across a corpus of 300 million documents.
• Define a compelling vision, craft metrics that truly matter, and experiment your way to breakthrough features that redefine discovery in partnership with Engineering, Analytics, Data Science, Design, and ML teams.
• Chart the long-term recommendations strategy — own a multi-year roadmap spanning candidate generation, ranking, and results presentation across Scribd surfaces.
• Partner with ML Engineering & Applied Research — translate cutting-edge retrieval and ranking research into production systems blending signals, embeddings, and real-time data.
• Define the metrics that matter — establish and monitor leading indicators of recommendations success: engagement rate, click-through, content completion, and subscription metrics.
• Balance short-term wins with long-term vision — ship incremental relevance improvements that hit revenue goals while building an extensible platform.
• Fuse data with the voice of the customer — synthesize experiment results and feedback to inform prioritization and design.
• Communicate with clarity and influence — align product, engineering, design, content, and executives on requirements, timelines, deliverables, and impact.

Skills

Product management

Retrieval algorithms

Ranking algorithms

Embeddings

Feature stores

LLM-powered workflows

SQL copilots

Data exploration tools

GenAI‑enhanced discovery

ML ops tooling

Education

Bachelor’s degree in CS/Engineering/Math

Tools

SQL copilots

Data exploration tools

ML ops tooling

Job description

Scribd seeks a senior product manager to own the recommendations experience for hundreds of millions of readers. You’ll shape the end-to-end discovery journey, balancing retrieval, ranking, and personalization with a scalable platform vision.

You’ll partner with ML, data science, design and engineering to define metrics, drive multi-year roadmaps, and ship ML-driven features that move engagement and revenue while guiding Scribd’s 3-year AI strategy.