Jobs at Scribd, Inc.

Own product and lifecycle growth marketing for Everand and Fable: define positioning and GTM, build and ship campaigns across email/push/in-app in Iterable, set metrics and tracking, iterate on messaging and targeting, and partner with Product and Brand to drive adoption and growth.

Lead development of the Fable Android app: design and build high-quality experiences, drive architecture and performance improvements, collaborate with product/design/QE, mentor engineers, improve code quality and release reliability, and own features from concept to release.

Own and set technical direction for the Everand backend, building scalable, reliable systems for discoverability, personalization, and core consumption journeys. Drive architecture, platform health (CI/CD, staging, DBs, queues, cost, observability), mentor engineers, lead cross-team planning, modernize legacy systems, and partner with product, design, analytics, web/mobile, and ML to support experimentation and telemetry-driven decisions.

Design, develop, and deploy machine learning and NLP solutions at scale. Work with cross-functional teams to build content classification, representation learning, search, and recommendation models using classical ML, deep learning, and LLMs. Process large datasets with Python, SQL, and Spark, and communicate results to stakeholders with clear documentation.

Lead analytics and operational insights for Customer Operations: define core metrics, build dashboards and forecasts, model churn/renewal risk, enable self-serve reporting, implement AI-enabled automation, and partner cross-functionally to drive retention, expansion, and support efficiency.

Lead technical direction and architecture for the Fable backend, own platform reliability (databases, CI/CD, queues, observability), run incident response and postmortems, mentor engineers, collaborate cross-functionally with product/design/ML, and build platform capabilities enabling faster, safer delivery.

Lead and scale paid social advertising across Meta, TikTok, Reddit, and emerging platforms to drive user acquisition for subscription products. Own budgets, audience targeting, structured testing, creative collaboration, AI-accelerated experimentation, analytics, attribution and incrementality work, and conversion rate optimization across landing pages. Communicate results and build reusable playbooks for the performance marketing team.

Join the Signup & Activation team to build and optimize frontend experiences that drive user acquisition and early activation. Collaborate with product, design, analytics, and backend engineers to implement high-quality, performant React/TypeScript interfaces, run experiments (A/B testing and personalization), and own well-scoped features from design through delivery in a Rails-backed environment.

Design, implement, and scale event-driven, distributed backend systems in Python on AWS to process and enrich large-scale document and media datasets. Lead technical projects, mentor engineers, integrate ML/LLM components, optimize performance, maintain observability, and collaborate with Data Science, ML Engineering, and Product to deliver reliable high-throughput content processing services.

Lead the product strategy for Scribd's internal developer and agentic platforms: unify AI workstreams, own internal app/plugin/agent runtimes, translate functional needs into platform requirements, drive cross-functional adoption and metrics, and run internal rollouts and evaluation to prove impact.

Lead design and scaling of content ingestion, metadata, and processing systems. Build reliable pipelines handling messy formats, collaborate with ML, security, and product teams, mentor engineers, and drive platform and AI/LLM integration for content workflows and quality.

Design and implement features for content ingestion pipelines, metadata services, and content processing workflows. Build reliable, observable services that handle diverse file formats, malformed inputs, retries, and asynchronous workflows. Collaborate with ML, Search & Discovery, and Product to improve metadata extraction, classification, and discoverability while leveraging LLM-based tools and AI-driven practices.

Build and optimize frontend signup and activation experiences using modern JavaScript and TypeScript. Collaborate with product, design, and analytics to implement high-converting, accessible, and performant user flows, own features from design through implementation, and participate in experimentation and personalization to improve conversion.

Lead product analytics for zero-to-one ML/LLM-powered experiences: define measurement frameworks, design and evaluate experiments, build instrumentation and KPI systems, partner with Product/ML/Engineering to drive data-informed product strategy and scalable dashboards.

Lead and grow a Data Engineering team to build production data pipelines, medallion datasets, and reusable data products. Drive architecture, engineering standards, design reviews, and cross-functional delivery. Partner with Product, Analytics, Data Science, and Platform to enable governed, reliable data foundations for analytics and AI. Mentor engineers and manage multiple concurrent initiatives to deliver predictable outcomes.

Lead zero-to-one transformation of Scribd's knowledge platform using ML/LLMs. Set product vision, roadmap, and success metrics; prioritize trade-offs; partner with Design, Engineering, ML, and Data Science; deliver incremental improvements and extensible platform capabilities; drive cross-functional alignment and measure core user journeys.

Lead strategy and execution for Scribd's Search product, defining multi-year roadmaps and metrics, partnering with ML, engineering, design, and analytics to ship ML-driven retrieval and ranking features that improve relevance, engagement, and conversion across large-scale consumer surfaces.