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

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.

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 Py Torch, Tensor Flow

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.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .

Pay & Benefits

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 $181,100 and $318,400, 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.