Staff Machine Learning Engineer – Ads Signals Intelligence & Information Retrieval

Summary

At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses! Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes—from small app developers to big, global brands. Because when advertising is done right, it benefits everyone!

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—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.

This role focuses on developing rich semantic signals from a variety of 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.

While ad tech knowledge is a strong bonus, the core of the role is building high-quality, privacy-centric signals that fuel some of Apple’s most advanced machine learning systems.

As part of the Ads Signals Intelligence team, you’ll be shaping the foundation of Apple’s ad ranking and relevance systems through world-class signal understanding. You’ll work on problems at the cutting edge of retrieval, multimodal learning, LLMs, and content intelligence—while contributing to Apple’s mission to deliver high-performing, privacy-first advertising experiences at scale.

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

Minimum Qualifications

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.

Preferred Qualifications

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.

Pay & Benefits — Cupertino, California, United States

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Application Deadline

Apple accepts applications to this posting on an ongoing basis.