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Description
We're is looking for a highly skilled and motivated Machine Learning Engineer to join our Predictions group. We build the core machine learning models that power ad predictions and monetization across Apple’s App Store and News platforms. The ideal candidate will bring deep expertise in machine learning, information retrieval, and large-scale modeling, and will thrive in a fast-paced, privacy-first environment. You’ll work at the intersection of applied ML, deep learning, and retrieval systems—developing models that predict user interaction, optimize marketplace outcomes, and scale across billions of queries. You'll also explore and operationalize emerging techniques in Large Language Models (LLMs), Reinforcement Learning, and representation learning to advance Apple’s ad prediction systems.
Minimum Qualifications
6+ years of experience applying machine learning and statistical modeling at scale, preferably in ad tech, recommender systems, or web-scale search/retrieval Deep experience with neural network architectures (e.g., Transformers, DNNs, RNNs) and training pipelines using TensorFlow, PyTorch Practical understanding of reinforcement learning, explore/exploit strategies, and bandit-based optimization Experience working with high-volume data pipelines, A/B testing infrastructure, and performance measurement at scale Proficient in Python and familiar with SQL, Scala, or Java for production environments Ability to translate abstract ideas into concrete, high-impact solutions Bachelor's, or equivalent experience, in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field.
Preferred Qualifications
MS or PhD, or equivalent experience, in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field. Great foundation in information retrieval, including query-document matching, embedding-based ranking, and learning-to-rank algorithms is a plus
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