Apple Ads is looking to develop the next generation of ML signal platforms to power retrieval, prediction, and relevance across Apple's advertising ecosystem. This involves building content understanding systems and large-scale infrastructure for near real-time signal updates to enable smarter, privacy-aware decision-making in the ad delivery stack.
Requirements
- 3+ years of experience in ML 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
- Demonstrated ability to deliver high-impact ML solutions in production environments
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 use 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
- Bachelor's degree, or equivalent experience, in Computer Science, Machine Learning, Information Retrieval, NLP, or a related field or experience
- 5+ years of experience in ML or applied research, with a focus on retrieval, ranking, NLP, or content understanding
- Exposure to ad tech domains such as auction modeling, targeting, attribution, or creative optimization
- MS or PhD, or equivalent experience, in Computer Science, Machine Learning, Information Retrieval, NLP, or a related field
