Apple Inc.
Description
Cupertino, California, United States Software and Services
Apple Ads is Hiring a hands-on Machine Learning Engineer. In this role you will build design and build Machine learning systems and data pipelines to safeguard the advertiser trust of our platform and enhance invalid traffic protections. You will define and execute an innovation roadmap; build and deploy 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.
Responsibilities
Develop Offline and Online Inference Models for large scale data.
Design, develop, and optimize distributed algorithms and data processing frameworks(e.g. Spark).
Implement scalable feature pipelines to ingest, clean, transform, and analyze massive datasets.
Solve complex problems with multilayered data sets, and optimize existing machine learning libraries and frameworks
Stay up to date with developments in the machine learning industry
Collaborate with product and engineering teams on production systems and 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.
Minimum Qualifications
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.
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.
BS or MS in Computer Science, Software Engineering or related technical fields.
Preferred Qualifications
7+ years of experience building machine learning capabilities across many different product areas at scale.
Background in Advertising systems.
Contributions to open-source algorithm frameworks or data processing tools.
Prior experience working with Anomaly detection is a plus.
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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Apple Ads is Hiring a hands-on Machine Learning Engineer. In this role you will build design and build Machine learning systems and data pipelines to safeguard the advertiser trust of our platform and enhance invalid traffic protections. You will define and execute an innovation roadmap; build and deploy 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.
Responsibilities
Develop Offline and Online Inference Models for large scale data.
Design, develop, and optimize distributed algorithms and data processing frameworks(e.g. Spark).
Implement scalable feature pipelines to ingest, clean, transform, and analyze massive datasets.
Solve complex problems with multilayered data sets, and optimize existing machine learning libraries and frameworks
Stay up to date with developments in the machine learning industry
Collaborate with product and engineering teams on production systems and 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.
Minimum Qualifications
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.
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.
BS or MS in Computer Science, Software Engineering or related technical fields.
Preferred Qualifications
7+ years of experience building machine learning capabilities across many different product areas at scale.
Background in Advertising systems.
Contributions to open-source algorithm frameworks or data processing tools.
Prior experience working with Anomaly detection is a plus.
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.
#J-18808-Ljbffr