Senior Machine Learning Engineer - Matching, Apple Ads

Apple Inc.; Cupertino (CA); On-site; USD 184,700 - 277,600; Full time

Job summary

Apple Inc. in Cupertino, CA is seeking a Senior Machine Learning Engineer for Matching within Apple Ads to design and implement ML algorithms for our retrieval system, improving ad relevance and scale across services such as the App Store and Apple News.

You will own end‑to‑end ideation, development, testing, and productization of these algorithms, collaborating with product and business leadership. This role requires 4+ years of experience, strong NLP/IR foundations, and a privacy‑conscious,

Qualifications

• 4+ years of experience building ML capabilities at scale across product areas.
• Proven experience in NLP, information retrieval and search.
• Ability to apply research concepts in production‑level code.
• Experience defining clear, testable research hypotheses with business impact.
• Deep understanding of experimental design and online experimentation at scale.
• Experience contributing to or reviewing research for top conferences/publications.
• Master's, or equivalent, in NLP/ML/Statistics/Forecasting/Optimization or RL with production systems exposure.

Responsibilities

• Develop algorithms for our ads retrieval system and iterate on model improvements.
• Own end‑to‑end ideation, development, testing and productization of these algorithms.
• Work with cross‑functional teams to ensure feasibility, privacy compliance, and robustness.
• Present findings across the organization and contribute to strategic roadmap discussions.

Skills

NLP

Information retrieval

Production code

Design of experiments

Online experimentation

Research publications

Collaboration

Education

Master's or PhD in NLP/ML/Statistics/Forecasting/Optimization/RL

Job description

Senior Machine Learning Engineer - Matching, Apple Ads

Cupertino, California, United States Software and Services

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! You’ll have the opportunity to develop models that improve our platform across the board, write production code to generate recommendations, work closely with business partners to help drive the development of new products as well as perform large scale and complex experiments to understand their effects. You’ll drive strategic outcomes through substantial innovation in multiple fields by leading the development and application of advanced techniques and algorithms to improve our ad network. You’ve, or will develop a deep understanding of the ad network behavior, and will work with product management and business leadership to prioritize an innovation roadmap across multiple technical domains. You’ll lead the conception, development, and delivery of state of the art capabilities that differentiate our products and are core to our business. You should have experience developing and implementing machine learning algorithms, ideally within the ads space. You’ll have an excellent understanding of scalable architectures and thrive working in Agile environments. The ability to be a good team player under tight deadline constraints is key to success.

Description

Matching at Ads is a critical component of our Ads funnel and responsible for ensuring that we are retrieving relevant and engaging Ads for our users. We are building the next generation of our retrieval systems to sustain the growth of the business for the future. We are looking for a Machine Learning Engineer that will develop the algorithms for our retrieval system. In this role you will drive step-change improvements in our outcomes, impact our platform revenue and quality of our ads, and formulate approaches to greenfield product opportunities. You will own end-to-end the ideation, development, testing and productization of these algorithms. You will work with complex problems in the ads retrieval space, provide solution that adhere to Apple’s privacy principles, review and contribute to state of the art in research, work with a variety of cross functional teams to ensure the feasibility and robustness of delivering new capabilities. This role will work closely with organizational partners and be expected to present findings across the organization.

Minimum Qualifications

• 4+ years of experience building machine learning capabilities across many different product areas at scale.
• Proven experience in NLP, information retrieval and search.
• Ability to apply and implement research concepts, ultimately in production quality code.
• Experience defining clear, testable research hypotheses, including intended impact on the business.
• Deep understanding of design of experiments, online experimentation approaches, preferably at scale.
• Experience contributing and/or reviewing research for top conferences and publications.
• Master's, or equivalent experience, in NLP, Machine Learning, Statistics, Forecasting, Optimization, Reinforcement Learning or related field with experience building production systems or have equivalent experience working with large data science / machine learning projects in industry.

Preferred Qualifications

• 7+ years of experience building machine learning capabilities across many different product areas at scale.
• PhD, or equivalent experience, in NLP, Machine Learning, Deep Learning, Large Language Model, Reinforcement Learning or related field with experience building production systems or have equivalent experience working with large data science / machine learning projects in industry.

Compensation and 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 $184,700 and $277,600, 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.

Equal Opportunity, Diversity, and Accessibility

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.

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace.

Learn about reasonable accommodations for job applicants.