Machine Learning Engineer Ads Signals Intelligence & Information Retrieval (Cupertino)

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 sourcesincluding queries, creatives, metadata, and user interactionsto 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.

- 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, infrastructure, and product teams to productionize systems while meeting Apples high standards for reliability and privacy.

Minimum Qualifications

• 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 ML frameworks like PyTorch, TensorFlow.
• Background in statistical modeling, optimization, and ML theory.
• Demonstrated ability to deliver high-impact ML solutions in production environments.
• Bachelor's degree, or equivalent experience, in Computer Science, Machine Learning, Information Retrieval, NLP, or a related field or experience.

Preferred Qualifications

• 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.

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 Apples 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.