Staff Machine Learning Engineer – Ads Signals Intelligence & Information Retrieval

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. 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!

Apples Ads Signals Intelligence team is seeking a hands-on and experienced Machine Learning Engineer to develop the next generation of ML-driven signal platforms that power retrieval prediction and relevance across Apples advertising ecosystemincluding the App Store and Apple News. This role focuses on building content understanding systems and large-scale infrastructure capable of delivering near real-time signal updates enabling smarter privacy-aware decision-making throughout the ad delivery role focuses on developing rich semantic signals from a variety of sourcesincluding queries creatives metadata and user interactionsto support scalable ad retrieval creative ranking and marketplace optimization. Youll work at the forefront of LLM fine-tuning knowledge graph construction semantic search and multimodal representation learning to extract structured intelligence from unstructured ad tech knowledge is a strong bonus the core of the role is building high-quality privacy-centric signals that fuel some of Apples most advanced machine learning part of the Ads Signals Intelligence team youll be shaping the foundation of Apples ad ranking and relevance systems through world-class signal understanding. Youll work on problems at the cutting edge of retrieval multimodal learning LLMs and content intelligencewhile contributing to Apples mission to deliver high-performing privacy-first advertising experiences at scale.

Design implement and scale ML systems that extract high-value semantic signals from structured and unstructured content nContribute to retrieval and ranking pipelines using techniques in query understanding semantic embedding and dense/sparse indexing nFine-tune and apply Large Language Models (LLMs) for NLP tasks like content labeling rewriting and semantic similarity nConstruct and utilize knowledge graphs and entity linking systems for enriching creative and query signals nWork with multimodal data (e.g. combining text image and metadata signals) to build robust cross-domain signal representations nBuild core components for a content understanding platform such as entity extraction topic modeling creative summarization and taxonomy generation nOwn experimentation offline evaluation and online validation of signal pipelines at massive scale nCollaborate across engineering infra and product teams to productionize systems while meeting Apples high standards for reliability and privacy

4 years of experience in machine learning or applied research with a focus on retrieval ranking NLP or content understanding nDeep understanding of information retrieval semantic search and query-document matching nStrong hands-on experience with LLM fine-tuning knowledge graph construction and entity-centric modeling nExperience working with multimodal models including text vision metadata or audio-based representations nProficiency in Python and experience with one or more of ML frameworks like PyTorch TensorFlow nBackground in statistical modeling optimization and ML theory nExposure to ad tech domains such as auction modeling targeting attribution or creative optimization is a plusnDemonstrated ability to deliver high-impact ML solutions in production environments nBachelors in Computer Science Machine Learning Information Retrieval NLP or a related field.

7 years of experience in machine learning or applied research with a focus on retrieval ranking NLP or content understanding nMS or PhD in Computer Science Machine Learning Information Retrieval NLP or a related field.