Apple Ads is looking 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.
Requirements
- 4+ years of experience in machine learning or applied research, with a focus on retrieval, ranking, NLP, or content understanding
- Deep understanding of information retrieval, semantic search, and query-document matching
- Strong hands-on experience with LLM fine-tuning, knowledge graph construction, and entity-centric modeling
- Experience working with multimodal models, including text, vision, metadata, or audio-based representations
- Proficiency in Python, and experience with one or more of ML frameworks like PyTorch, TensorFlow
- Background in statistical modeling, optimization, and ML theory
- Exposure to ad tech domains such as auction modeling, targeting, attribution, or creative optimization is a plus
Responsibilities
- Design, implement, and scale ML systems that extract high-value semantic signals from structured and unstructured content
- Contribute to retrieval and ranking pipelines using techniques in query understanding, semantic embedding, and dense/sparse indexing
- Fine-tune and apply Large Language Models (LLMs) for NLP tasks like content labeling, rewriting, and semantic similarity
- Construct and utilize knowledge graphs and entity linking systems for enriching creative and query signals
- Work with multimodal data (e.g., combining text, image, and metadata signals) to build robust, cross-domain signal representations
- Build core components for a content understanding platform, such as entity extraction, topic modeling, creative summarization, and taxonomy generation
- Own experimentation, offline evaluation, and online validation of signal pipelines at massive scale
Other
- Collaborate across engineering, infra, and product teams to productionize systems while meeting Apple’s high standards for reliability and privacy
- Demonstrated ability to deliver high-impact ML solutions in production environments
- Bachelor'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
- MS or PhD in Computer Science, Machine Learning, Information Retrieval, NLP, or a related field.
