Machine Learning Engineering Intern (2027 Summer Internship)

About AppLovin AppLovin makes technologies that help businesses of every size connect to their ideal customers. The company provides end-to-end advertising solutions for businesses to reach, monetize and grow their global audiences. For more information about AppLovin, visit: www.applovin.com. To deliver on this mission, our global team is composed of team members with life experiences, backgrounds, and perspectives that mirror our developers and customers around the world. At AppLovin, we are intentional about the team and culture we are building, seeking candidates who are outstanding in their own right and also demonstrate their support of others. At AppLovin, AI isn't a feature — it's the foundation. We are building a next-generation global content platform that uses intelligent recommendation, personalisation, and content understanding to help people discover experiences that genuinely matter to them. Backed by AppLovin's world-class AI capabilities and global infrastructure, our ML team is working on some of the most technically interesting problems in the recommendation and content space — at a scale few startups ever reach. For Summer 2027, we're looking for Machine Learning Engineer Interns who want to work on real ML systems, not toy datasets. You'll contribute to production pipelines across areas like content recommendation, ranking, user modelling, and content quality — depending on where you're placed and where you can make the most impact. About Gist Gist is a new social media platform for people who want substance — practical, thoughtful content that spans philosophy debates, city-specific recommendations, seasonal gift guides, and wellness tips. Across categories like travel, food, career, and family, we describe it as "a handbook for the curious". About the Team Our ML team owns the intelligence layer of the platform — the systems that decide what content a user sees, how it's ranked, how new users and new content are onboarded, and how we balance engagement, retention, and ecosystem health over time. It's a highly cross-functional team: you'll work alongside product managers, backend engineers, and data analysts to turn model improvements into measurable business outcomes. As an intern, you'll be embedded in a specific ML workstream with a senior engineer mentor and a project scoped for real production impact. What You’ll Do • Contribute to the development and evaluation of ML models within a defined area — recommendation, ranking, content understanding, or user behaviour modelling. • Own a focused internship project end-to-end: problem framing, feature engineering, model training, offline evaluation, and where possible, online experimentation. • Run experiments and analyse results to form a clear, data-backed view of what's working and why. • Collaborate with engineers and product managers to understand system constraints and translate model improvements into production-ready solutions. • Participate in team discussions on model architecture, system design, and metric trade-offs. Requirements • Currently pursuing a Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field • Solid foundation in machine learning concepts — supervised learning, model evaluation, optimisation, and the trade-offs between different modelling approaches. • Proficiency in Python and familiarity with at least one ML framework such as PyTorch or TensorFlow. • Comfortable working with data — feature engineering, exploratory analysis, and interpreting experimental results. • Strong software engineering fundamentals: clean code, version control, and the ability to collaborate on a shared codebase. • Curious, rigorous, and honest about what the data is actually telling you. Good To Have • Any project or coursework experience applying ML to real data — Kaggle competitions, research projects, and course capstones all count. • Exposure to recommendation systems, ranking, or personalisation concepts — even from an academic or reading background. • Familiarity with large-scale data tools such as Spark, Hive, or cloud ML platforms. • Understanding of A/B testing and statistical significance in an experimentation context. • Interest in content platforms, social products, or AI-driven discovery systems. AppLovin is proud to be an equal opportunity employer that is committed to inclusion and diversity. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status, or other legally protected characteristics. Learn more about EEO rights as an applicant here. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send us a request at jobs@applovin.com AppLovin will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in California, learn more here. To support an efficient and fair hiring process, we may use technology-assisted tools, including artificial intelligence (AI), to help identify and evaluate candidates. All hiring decisions are ultimately made by human reviewers. Please read our Global Applicant Privacy Notice to learn more about how AppLovin processes your personal information. #J-18808-Ljbffr