Senior Machine Learning Engineer – Ads Predictions

At Apple we focus deeply on our customers experience. Apple Ads brings this same approach to advertising helping people find exactly what theyre looking for and helping advertisers grow their businesses! nnOur technology powers ads and sponsorships across Apple Services including the App Store Apple News and MLS Season Pass. Everything we do is designed for trust connection and impact: We respect user privacy integrate advertising thoughtfully into the experience and deliver value for advertisers of all sizesfrom small app developers to big global brands. Because when advertising is done right it benefits everyone!

Were 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 Apples 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 work at the intersection of applied ML deep learning and retrieval systemsdeveloping models that predict user interaction optimize marketplace outcomes and scale across billions of queries. Youll also explore and operationalize emerging techniques in Large Language Models (LLMs) Reinforcement Learning and representation learning to advance Apples ad prediction systems.n

Design and implement ML models to improve predictions of user interaction click-through rate (CTR) and conversion rate (CVR)nDevelop and optimize retrieval algorithms leveraging techniques from classical IR and modern deep learningnContribute to core modeling areas such as deep neural networks contextual bandits multi-task learning and LLM-based ranking signalsnWork with large-scale distributed datasets to identify new signals and improve model accuracy and robustnessnCollaborate with cross-functional teams across engineering infrastructure and product to scale models to productionnParticipate in designing and running large-scale experiments to validate new model architectures and learning strategies

6 years of experience applying machine learning and statistical modeling at scale preferably in ad tech recommender systems or web-scale search/retrievalnDeep experience with neural network architectures (e.g. Transformers DNNs RNNs) and training pipelines using TensorFlow PyTorchnPractical understanding of reinforcement learning explore/exploit strategies and bandit-based optimizationnExperience working with high-volume data pipelines A/B testing infrastructure and performance measurement at scalenProficient in Python and familiar with SQL Scala or Java for production environmentsnAbility to translate abstract ideas into concrete high-impact solutions nBachelors or equivalent experience in Computer Science Machine Learning Artificial Intelligence Information Retrieval or a related field.

MS or PhD or equivalent experience in Computer Science Machine Learning Artificial Intelligence Information Retrieval or a related foundation in information retrieval including query-document matching embedding-based ranking and learning-to-rank algorithms is a plus