Machine Learning Engineer - Ads

14 Minutes ago • 4 Years + • $147,400 PA - $272,100 PA
Research Development

Job Description

At Apple, the Ads team focuses on customer experience, powering ads and sponsorships across Apple Services like the App Store and Apple News. They seek a strategic Machine Learning Engineer to innovate across a modern, large-scale platform. This role involves designing, building, and operating real-time ML systems and data pipelines for prediction and decisioning, spanning personalization, ranking, allocation, and optimization, while maintaining privacy and safety standards. The engineer will define innovation roadmaps, productionize models with robust CI/CD, feature stores, and streaming infrastructure, and run A/B experimentation to deliver measurable improvements.
Good To Have:
  • Prior experience working with machine learning platforms or real-time recommendation engines is a plus.
  • 7+ years of experience building machine learning capabilities across many different product areas at scale.
  • Background in Advertising systems.
  • Hands-on experience with service reliability engineering (SRE) and SLA monitoring.
  • Contributions to open-source algorithm frameworks or data processing tools.
Must Have:
  • Design, develop, and optimize distributed algorithms and data processing frameworks (e.g., Spark).
  • Implement scalable data pipelines to ingest, clean, transform, and analyze massive datasets.
  • Collaborate with machine learning engineers to deploy and operationalize algorithms in production.
  • Own the full lifecycle of services—from architecture to monitoring—for high-throughput, low-latency applications.
  • Drive performance optimization, bottleneck analysis, and system tuning across compute and storage layers.
  • Build tools to support A/B testing, statistical evaluation, and experimentation pipelines.
  • Ensure data integrity, security, and compliance across all solutions.
  • Participate in cross-functional Agile teams to prototype and deliver impactful, data-driven products.
Perks:
  • Comprehensive medical and dental coverage
  • Retirement benefits
  • A range of discounted products and free services
  • Reimbursement for certain educational expenses (including tuition) for formal education related to advancing your career at Apple
  • Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
  • Eligibility for discretionary restricted stock unit awards
  • Ability to purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan
  • Eligibility for discretionary bonuses or commission payments
  • Relocation assistance

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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!

The Apple Ads team is seeking a strategic, hands-on Machine Learning Engineer to drive innovation across a modern, large-scale platform. You will design, build, and operate real-time ML systems and large-scale data pipelines that power end-to-end prediction and decisioning—spanning personalization, retrieval/ranking, allocation, and optimization—while upholding strong reliability, privacy, and safety standards. You’ll define and execute an innovation roadmap; productionize models with robust CI/CD, feature stores, and streaming infrastructure (e.g., Kafka/Spark/Flink); and run A/B experimentation. You will lead performance tuning, calibration, and drift detection to deliver measurable improvements in product quality, user experience, latency, and cost. This role rewards ownership from architecture through monitoring and SLAs, with influence across adjacent areas such as recommendations, response prediction, and experimentation tooling.

  • 4+ years of experience building machine learning capabilities across many different product areas at scale
  • Strong proficiency in Java, Python, or Scala for algorithm and system development.
  • Experience with distributed systems and big data frameworks such as Spark, Kafka, Hadoop, or Flink.
  • Solid understanding of data structures, algorithms, and system design principles.
  • Expertise in working with relational databases (PostgreSQL, MySQL, Oracle) and NoSQL/Cloud storage (S3, GCS, etc.).
  • Familiarity with CI/CD workflows, cloud environments, and containerized deployments.
  • Knowledge of data validation, cleansing, and quality assurance practices.
  • Understanding of statistical methods, A/B testing, and online experimentation frameworks.
  • Prior experience working with machine learning platforms or real-time recommendation engines is a plus.
  • BS or MS in Computer Science, Software Engineering or related technical fields.
  • Design, develop, and optimize distributed algorithms and data processing frameworks (e.g., Spark).
  • Implement scalable data pipelines to ingest, clean, transform, and analyze massive datasets.
  • Collaborate with machine learning engineers to deploy and operationalize algorithms in production.
  • Own the full lifecycle of services—from architecture to monitoring—for high-throughput, low-latency applications.
  • Drive performance optimization, bottleneck analysis, and system tuning across compute and storage layers.
  • Build tools to support A/B testing, statistical evaluation, and experimentation pipelines.
  • Ensure data integrity, security, and compliance across all solutions.
  • Participate in cross-functional Agile teams to prototype and deliver impactful, data-driven products.
  • 7+ years of experience building machine learning capabilities across many different product areas at scale.
  • Background in Advertising systems.
  • Hands-on experience with service reliability engineering (SRE) and SLA monitoring.
  • Contributions to open-source algorithm frameworks or data processing tools.

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 $147,400 and $272,100, 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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