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Drives advertising product initiatives across campaign management, creative workflows, mobile app install, ecommerce, CTV, measurement, and partnerships. Designs advertiser experiences, manages pilot programs, analyzes product and campaign data using SQL, defines success metrics, conducts A/B testing, identifies growth opportunities, and influences roadmap decisions. Partners with Engineering, Design, Business Development, Growth, and Client Strategy teams to launch and measure product improvements.

Build and maintain responsive web applications, mobile WebView experiences, mini games, backend APIs, and database integrations. Collaborate with product, design, and mobile engineering teams to ship reliable features. Improve performance, stability, and user experience; write tested, maintainable code; participate in reviews; troubleshoot issues; and independently deliver at least one project to real users during the internship.

Build and maintain full-stack web applications, embedded WebView experiences, mini games, backend APIs, and database integrations. Partner with product, design, and mobile engineering teams to deliver responsive, reliable features from implementation through launch. Improve performance, stability, and user experience; write tested, maintainable code; participate in code reviews; and troubleshoot frontend and backend issues. Contribute to reusable components and the technical foundation of a growing consumer social application.

Build AppLovin’s China partner ecosystem for cross-border DTC advertising by identifying, closing, and activating agencies, platforms, payment providers, and influencers. Generate advertiser leads, manage partner performance and QBRs, coordinate onboarding and campaign support, develop enablement and co-marketing programs, and provide market intelligence to global teams. The role requires strong China e-commerce relationships, commercial partnership experience, Mandarin fluency, English proficiency, and occasional travel.

Manage business development and consultative sales for AppLovin’s Axon advertising platform across consumer apps, eCommerce, subscription, retail, and lead-generation clients. Build executive and agency relationships, identify growth opportunities, manage sales pipelines and forecasts, secure platform adoption, and drive revenue. Collaborate with product, marketing, technical services, client services, and supply teams on integrations, betas, commercialization, and roadmap feedback. Represent AppLovin at industry events and support client success across North America.

Manages office operations and administrative activities. The provided description contains no specific duties, qualifications, compensation, travel, or clearance requirements beyond the Office Manager title.

Own a focused product project from problem framing and user research through execution and measurement. Analyze user behavior, product metrics, and experiments; collaborate with engineers and designers to define requirements and ship features. Contribute insights on user growth, content contribution, discovery, and creator incentives in a fast-moving social platform environment.

Develop and evaluate machine learning models for recommendation, ranking, content understanding, and user behavior modeling. Own an end-to-end internship project involving problem framing, feature engineering, training, evaluation, experimentation, and potentially production deployment. Analyze results, collaborate with engineering and product teams, and contribute to discussions on model architecture, system design, and performance trade-offs.

Develops client-focused video stories for AppLovin, from research and narrative development through interviewing, production, editing, and delivery. The role owns end-to-end video production, collaborates with Design on visual direction, manages production workflows, and travels for shoots. Candidates need strong storytelling, editing judgment, production adaptability, self-direction, and a portfolio demonstrating at least five years of high-quality video content creation.

Develop and deploy large-scale machine learning systems for advertising and recommendation, including user signals, representation learning, ranking, retrieval, prediction, and optimization. Build scalable models, training infrastructure, evaluation tools, and production systems. Improve data and feature quality, model performance, training and inference efficiency, and system reliability. Collaborate with engineering, data, and product teams to move ML innovations from experimentation into production.