Senior Machine Learning Engineer - Ads Signals Intelligence & Information Retrieval

Job Description

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.

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
• 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

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
• Collaborate across engineering, infra, and product teams to productionize systems while meeting Apple’s high standards for reliability and privacy

Benefits

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.