Senior Machine Learning Engineer Ads Relevance & Quality

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! Our technology powers ads and sponsorships across Apple Services including the App Store Apple News and MLS Season Pass. nnEverything 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!nnApples Ads team is seeking a highly skilled and motivated Machine Learning Engineer to join the Ads Relevance and Quality team. This team is responsible for ensuring high-quality trustworthy ad experiences by building intelligent systems to evaluate ad relevance detect low-quality or offensive content and optimize user work at the intersection of applied ML NLP and content qualitydesigning models and systems that understand queries flag inappropriate content and raise the bar for ad relevance and user trust across billions of queries and impressions.

Youll play a key role in shaping the future of safe high-quality advertising at Apple. Your work will help ensure that ads remain useful relevant and respectful of our userssupporting Apples values of privacy trust and transparency. Youll collaborate with world-class engineers and researchers apply cutting-edge ML techniques in real-world systems and have a direct impact on the experience of millions of users every day.

Design and implement machine learning models to evaluate and improve ad relevance trust and quality for user queriesnBuild NLP and multi-modal models that detect offensive unsafe or policy-violating content at scalenDevelop methods for semantic query understanding ads understanding relevance scoring and keyword-to-ad matchingnCollaborate closely with product and policy teams to translate content integrity standards into measurable ML objectivesnWork with large-scale privacy-preserving datasets to discover and operationalize new quality signalsnConduct offline/online experiments to measure impact on user trust and satisfaction across AdsnPartner cross-functionally with infrastructure product and moderation teams to deploy models at production scale

4 years of experience applying machine learning at scale in domains such as ad tech content moderation search ranking or recommendation systemsnStrong expertise in natural language processing including offensive content detection semantic matchingnExperience with Transformer-based architectures (e.g. BERT DistilBERT) and training pipelines in TensorFlow or PyTorchnFamiliarity with fine-tuning Large Language Models (LLMs) for downstream tasks such as classification content moderation or semantic relevancenFamiliarity with quality and fairness evaluation frameworks (precision recall coverage policy alignment etc.)nHands-on experience with A/B testing experimentation frameworks and performance debugging in productionnProficiency in Python and SQLnStrong problem-solving and communication skills with a focus on translating abstract trust/safety goals into deployable solutionsnMS in Computer Science Machine Learning NLP or a related technical field

7 years of experience applying machine learning at scale in domains such as ad tech content moderation search ranking or recommendation systemsnPhD in Computer Science Machine Learning NLP or a related technical fieldnAdditional experience in Scala or Java