New York City, New York, United States Machine Learning and AI
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 representationsThis 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.- 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
- 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 of 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. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $143,100 and $264,200, 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.
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 .
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