{"schemaVersion":"jobsearcher.job.v1","id":"a35fb976180100e70e811c17","url":"https://jobsearcher.com/jobs/a35fb976180100e70e811c17","canonicalUrl":"https://jobsearcher.com/jobs/a35fb976180100e70e811c17","title":"Software Engineer, Data & Machine Learning Systems","description":"Imagine shaping how millions of people discover content they love on the App Store, Apple Music, and Apple TV+. Our team is responsible for the intelligence that powers these deeply personal experiences.\n\nWe are at a pivotal moment, defining the next generation of personalization. We build the foundational capabilities that empower product and research teams to deliver hyper-personalized experiences while maintaining an uncompromising commitment to user privacy. We believe that deep personalization shouldn't require compromising user trust, and we are pioneering the decentralized data systems to prove it.\n\nDescription\n\nThis is not a standard Data Engineering or Machine Learning role. We are looking for a pioneering engineer to join our team. You will build the systems that securely process, combine, and deliver the critical user and content signals needed for personalization, spanning from edge devices to cloud backends. You will engineer high-performance stacks that transform raw data into governed, discoverable intelligence, ensuring that machine learning models can seamlessly and securely access the right user and content signals regardless of where that data physically resides.\",\"responsibilities\":\"Architect Hybrid Feature Resolution: Design and build the access layer that abstracts the physical location of data. Ensure that inference systems can seamlessly access real-time on-device context, cloud-based service history, and content metadata through a unified, familiar API.\n\nEngineer Signal Fusion: Build robust, petabyte-scale pipelines that ingest and fuse disparate signals into coherent user profiles and rich content representations.\n\nArchitect the Semantic Data Layer: Transform raw data into the high-value signals that train our next-generation ML models. Architect the systems that generate this data and seamlessly integrate it with our training infrastructure.\n\nOptimize for Privacy & Scale: Build highly optimized stacks that extend existing data systems into privacy-constrained environments. Implement data minimization strategies to securely leverage rich user signals without compromising trust.\n\nCross-Functional Innovation: Partner closely with data systems teams, core compute engineers, and ML teams to ensure the right context is delivered to the right compute environment at the exact right time.\n\nPreferred Qualifications\n\nHybrid/Edge Computing: Experience building systems that bridge cloud backend systems with on-device or edge compute environments.\n\nEmbeddings & Vector Search: Familiarity with generating, managing, and serving dense embeddings for retrieval, ranking, and personalization systems.\n\nData Governance: Experience building semantic layers, data catalogs, or implementing compliance-by-design in a regulated environment.\n\nPrivacy-Preserving Tech: Passion for privacy and an understanding of data minimization strategies, secure enclaves, or Privacy-Enhancing Technologies (PETs).\n\nMinimum Qualifications\n\nBS or MS in Computer Science, Data Engineering, Software Engineering, or a related field.\n\nSenior-Level Experience: A proven track record of shipping complex, large-scale data engineering, feature serving, or machine learning systems to production.\n\nMastery of Big Data & Serving: Expertise in designing distributed data processing systems using technologies like Spark and Flink, and building low-latency, high-throughput data serving layers or Feature Stores.\n\nStrong Software Engineering: Deep proficiency in Java or Go for building high-performance production backend systems, and Python for model training ecosystems.\n\nStrategic Data Mindset: Demonstrated experience thinking critically about data architecture, including data ontology, discoverability, and bridging distributed data sources.\n\nApple 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 .\n\nPay & Benefits\n\nAt 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 $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location.\n\nApple 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.\n\nNote: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.","company":"Apple","rawCompany":"apple","city":"Seattle","state":"WA","isRemote":false,"isActive":false,"createdAt":"2026-07-15T14:19:49.794Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Software Engineer, Data & Machine Learning Systems","description":"Imagine shaping how millions of people discover content they love on the App Store, Apple Music, and Apple TV+. Our team is responsible for the intelligence that powers these deeply personal experiences.\n\nWe are at a pivotal moment, defining the next generation of personalization. We build the foundational capabilities that empower product and research teams to deliver hyper-personalized experiences while maintaining an uncompromising commitment to user privacy. We believe that deep personalization shouldn't require compromising user trust, and we are pioneering the decentralized data systems to prove it.\n\nDescription\n\nThis is not a standard Data Engineering or Machine Learning role. We are looking for a pioneering engineer to join our team. You will build the systems that securely process, combine, and deliver the critical user and content signals needed for personalization, spanning from edge devices to cloud backends. You will engineer high-performance stacks that transform raw data into governed, discoverable intelligence, ensuring that machine learning models can seamlessly and securely access the right user and content signals regardless of where that data physically resides.\",\"responsibilities\":\"Architect Hybrid Feature Resolution: Design and build the access layer that abstracts the physical location of data. Ensure that inference systems can seamlessly access real-time on-device context, cloud-based service history, and content metadata through a unified, familiar API.\n\nEngineer Signal Fusion: Build robust, petabyte-scale pipelines that ingest and fuse disparate signals into coherent user profiles and rich content representations.\n\nArchitect the Semantic Data Layer: Transform raw data into the high-value signals that train our next-generation ML models. Architect the systems that generate this data and seamlessly integrate it with our training infrastructure.\n\nOptimize for Privacy & Scale: Build highly optimized stacks that extend existing data systems into privacy-constrained environments. Implement data minimization strategies to securely leverage rich user signals without compromising trust.\n\nCross-Functional Innovation: Partner closely with data systems teams, core compute engineers, and ML teams to ensure the right context is delivered to the right compute environment at the exact right time.\n\nPreferred Qualifications\n\nHybrid/Edge Computing: Experience building systems that bridge cloud backend systems with on-device or edge compute environments.\n\nEmbeddings & Vector Search: Familiarity with generating, managing, and serving dense embeddings for retrieval, ranking, and personalization systems.\n\nData Governance: Experience building semantic layers, data catalogs, or implementing compliance-by-design in a regulated environment.\n\nPrivacy-Preserving Tech: Passion for privacy and an understanding of data minimization strategies, secure enclaves, or Privacy-Enhancing Technologies (PETs).\n\nMinimum Qualifications\n\nBS or MS in Computer Science, Data Engineering, Software Engineering, or a related field.\n\nSenior-Level Experience: A proven track record of shipping complex, large-scale data engineering, feature serving, or machine learning systems to production.\n\nMastery of Big Data & Serving: Expertise in designing distributed data processing systems using technologies like Spark and Flink, and building low-latency, high-throughput data serving layers or Feature Stores.\n\nStrong Software Engineering: Deep proficiency in Java or Go for building high-performance production backend systems, and Python for model training ecosystems.\n\nStrategic Data Mindset: Demonstrated experience thinking critically about data architecture, including data ontology, discoverability, and bridging distributed data sources.\n\nApple 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 .\n\nPay & Benefits\n\nAt 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 $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location.\n\nApple 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.\n\nNote: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.","datePosted":"2026-07-15T14:19:49.794Z","dateModified":"2026-07-15T14:19:49.794Z","hiringOrganization":{"@type":"Organization","name":"Apple","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Seattle","addressRegion":"WA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"a35fb976180100e70e811c17"},"url":"https://jobsearcher.com/jobs/a35fb976180100e70e811c17"}}