Software Engineering Intern, Apple Ads (Machine Learning)

As a Software Engineering Intern within the Apple Ads team, you will contribute to the design, development, and optimization of our advertising platforms, with a particular focus on leveraging machine learning to enhance ad relevance, performance, and user experience. You will work alongside experienced engineers on challenging projects, gaining hands-on experience with large-scale data, machine learning models, and distributed systems. Responsibilities may include developing and deploying machine learning algorithms, analyzing data to identify insights, writing clean and efficient code for production systems, participating in code reviews, debugging issues, and collaborating with cross-functional teams to deliver high-quality, privacy-preserving advertising solutions. Minimum Qualifications Currently pursuing a PhD in Computer Science, Software Engineering, Machine Learning, Data Science, or a related technical field. Strong foundational knowledge in data structures, algorithms, and object-oriented programming. Proficiency in at least one programming language commonly used in machine learning or backend development (e.g., Python, Java, Scala, C++). Understanding of fundamental machine learning concepts and statistical methods. Excellent problem-solving and analytical skills, with an ability to analyze complex data. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). Familiarity with large-scale data processing technologies (e.g., Spark, Hadoop, Flink) and distributed systems. Knowledge of database systems (SQL/NoSQL) and data warehousing concepts. Prior coursework or projects related to advertising technology, recommender systems, natural language processing, or computer vision. Familiarity with version control systems (e.g., Git). Preferred Qualifications Ability to work independently and as part of a collaborative team Strong communication and interpersonal skills, with an ability to articulate technical concepts. Demonstrated ability to learn new technologies quickly and adapt to evolving project requirements.