{"id":3839635,"url":"https://alion.io/job/apple-staff-machine-learning-engineer-matching-apple-ads","title":"Staff Machine Learning Engineer - Matching, Apple Ads","company":{"id":12,"name":"Apple","domain":"apple.com","url":"https://alion.io/company/apple","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Apple Jobs","truth_index":{"grade":"A","score":89,"open_postings":835,"ghost_share":0,"stale_share":0.217,"repost_share":0.006,"time_to_fill_p50_days":90,"computed_at":"2026-11-09T06:03:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cupertino, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Design of Experiments","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Reinforcement Learning","optional":false}],"status":"live","first_seen_at":"2026-11-05T21:18:45Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-09T08:53:54Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"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.\nEverything 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!\nYou'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.\nYou'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.\nDescription\nMatching 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.\nIn 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.\nMinimum Qualifications\n7+ years of experience building machine learning capabilities across many different product areas at scale.\nProven experience in NLP, information retrieval and search.\nAbility to apply and implement research concepts, ultimately in production quality code.\nExperience defining clear, testable research hypotheses, including intended impact on the business.\nDeep understanding of design of experiments, online experimentation approaches, preferably at scale.\nExperience contributing and/or reviewing research for top conferences and publications.\nMaster'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.\nPreferred 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