Machine Learning Engineer, Apple Ads

Apple Inc.
Cupertino, CA, United States
5 days ago
Apply on www.juju.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
4 years minimum
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) A/B Testing Agile Methodology Big Data Continuous Integration Data Validation Data Integrity Data Structures Distributed Systems Apache Hadoop Python (Programming Language) Machine Learning
+22 more
Open Source Technology Performance Tuning Systems Development Life Cycle Software Engineering Data Streaming Feature Store Data Processing Cloud Platform System Apache Spark Build Management Containerization Information Technology Low Latency Apache Flink Data Analytics Integration Frameworks Apache Kafka Build Tools Machine Learning Operations Drift Detection Data Pipelines Software Library

Job description

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., * Develop and manage end-to-end lifecycle of machine learning models, including observability for large-scale, high-throughput, and low-latency production systems.

  • 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.

Requirements

  • 4+ years of work 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., * 7+ years of work 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.

Benefits & conditions

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
  • 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.

About the company

At Apple, we focus deeply on the customer 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, MLS Season Pass and now F1! 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 news publishers to big, global brands. Because when advertising is done right, it benefits everyone.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.juju.com
Prepare application

Good distractions

Loading talks and stories from around this role…