Machine Learning Engineer – Ads Signals Intelligence & Information Retrieval

Cupertino, California, United States

Description

• 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.

This role focuses on developing rich semantic signals from various 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.

Minimum Qualifications

Preferred Qualifications

At Apple, base pay is one part of our total compensation package and is determined within a range. The base pay range for this role is between $147,400 and $272,100, depending on skills, qualifications, experience, and location.

Employees can participate in Apple’s stock programs, including stock purchase plans and restricted stock units, and receive benefits such as medical and dental coverage, retirement plans, discounts, and educational reimbursements. This role may also be eligible for bonuses, commissions, or relocation assistance. Learn more about Apple Benefits.

Note : Benefits, compensation, and stock programs are subject to eligibility and other terms.

Apple is an equal opportunity employer committed to diversity and inclusion. We promote equal opportunity regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristics. Learn more about your EEO rights as an applicant.

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