Machine Learning Engineering Summer Intern 2027

About the role

AppLovin is building a next‑generation global content platform powered by AI. As a Machine Learning Engineering Intern for the Summer 2027 cohort, you will work on real production pipelines that power content recommendation, ranking, user modelling, and content quality for the Gist social platform.

Key responsibilities

• Develop and evaluate ML models in a defined workstream such as recommendation, ranking, or user‑behaviour modelling.
• Own an end‑to‑end internship project, from problem framing and feature engineering to model training, offline evaluation and, when possible, online experimentation.
• Run experiments, analyse results and provide data‑backed insights on model performance.
• Collaborate with product managers and engineers to translate model improvements into production‑ready solutions.
• Participate in team discussions on model architecture, system design and metric trade‑offs.

Required profile

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics or a related field.
• Solid foundation in machine‑learning concepts, including supervised learning, model evaluation and optimisation.
• Proficiency in Python and experience 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, including clean code, version control and collaborative development.
• Curious, rigorous and honest about what the data is actually telling you.

Required skills

• Python programming
• PyTorch or TensorFlow
• Feature engineering and data preprocessing
• Version control (Git)
• Large‑scale data tools (e.g., Spark, Hive, cloud ML platforms)
• A/B testing and statistical significance analysis