What are the responsibilities and job description for the Staff Machine Learning Engineer - Ads Signals Intelligence & Information Retrieval position at Apple, Inc.?
At Apple, we focus deeply on our customers' experience. Apple Ads brings this same approach to advertising, helping people find exactly what they're 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 sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone!
Apple's 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 Apple's advertising ecosystem-including 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 stack.\n\nThis role focuses on developing rich semantic signals from a variety of sources-including queries, creatives, metadata, and user interactions-to support scalable ad retrieval, creative ranking, and marketplace optimization. You'll work at the forefront of LLM fine-tuning, knowledge graph construction, semantic search, and multimodal representation learning to extract structured intelligence from unstructured data.\n\nWhile ad tech knowledge is a strong bonus, the core of the role is building high-quality, privacy-centric signals that fuel some of Apple's most advanced machine learning systems.\n\nAs part of the Ads Signals Intelligence team, you'll be shaping the foundation of Apple's ad ranking and relevance systems through world-class signal understanding. You'll work on problems at the cutting edge of retrieval, multimodal learning, LLMs, and content intelligence-while contributing to Apple's mission to deliver high-performing, privacy-first advertising experiences at scale.
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 plus\nDemonstrated ability to deliver high-impact ML solutions in production environments \nBachelor's 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.
Apple's 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 Apple's advertising ecosystem-including 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 stack.\n\nThis role focuses on developing rich semantic signals from a variety of sources-including queries, creatives, metadata, and user interactions-to support scalable ad retrieval, creative ranking, and marketplace optimization. You'll work at the forefront of LLM fine-tuning, knowledge graph construction, semantic search, and multimodal representation learning to extract structured intelligence from unstructured data.\n\nWhile ad tech knowledge is a strong bonus, the core of the role is building high-quality, privacy-centric signals that fuel some of Apple's most advanced machine learning systems.\n\nAs part of the Ads Signals Intelligence team, you'll be shaping the foundation of Apple's ad ranking and relevance systems through world-class signal understanding. You'll work on problems at the cutting edge of retrieval, multimodal learning, LLMs, and content intelligence-while contributing to Apple's mission to deliver high-performing, privacy-first advertising experiences at scale.
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 plus\nDemonstrated ability to deliver high-impact ML solutions in production environments \nBachelor's 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.