We are seeking an experienced Machine Learning Engineer to drive innovation in ad prediction, quality, and privacy-preserving signals. This role spans three critical areas: building large-scale prediction models, designing signals that respect user privacy, and ensuring ad quality that aligns with Apple’s values of trust and transparency. You will set technical direction, lead complex initiatives, and mentor engineers while collaborating closely with research, infrastructure, and product teams. This role offers the opportunity to shape the future of privacy-first advertising at Apple. You’ll work with some of the best engineers and researchers in the field, solve problems at massive scale, and deliver models that respect users while driving meaningful outcomes for advertisers.

10+ years of experience applying ML at scale in ads, recommender systems, content ranking, or related domains.

Strong expertise in deep learning architectures (Transformers, LLMs, DNNs) and training frameworks (TensorFlow, PyTorch).

Proven track record in prediction systems (CTR, CVR, or related) and explore/exploit strategies (bandits, RL).

Experience with privacy-preserving ML (federated learning, differential privacy, homomorphic encryption, secure multiparty computation) is preferred.

Familiarity with large-scale data pipelines, A/B testing infrastructure, and production experimentation.

Strong coding skills in Python and production experience in at least one of: Scala, Java, C++.

Ability to set technical direction, influence cross-functional stakeholders, and deliver business impact.