Machine Learning Engineer, Ad Platforms

Santa Clara Valley (Cupertino), California, United States
Software and Services


Weekly Hours: 40
Role Number:200143561
At Apple, we work every day to create products that enrich people’s lives. Our Advertising Platforms group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in Search Ads in the App Store and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy. We are looking for an ambitious and versatile engineer who can thrive in an Agile environment, delivering solutions to enable advanced algorithms and techniques to improve an ad network. You will work closely with data scientists and other machine learning engineers to develop and implement platform components that will enable us to improve and scale our advertising algorithms. Platform components can range from core storage and processing capabilities and mission-critical pipelines, to exploratory analysis tools, model development and training infrastructure, to online inference architectures that react to real-time signals and preserve the privacy of our customers.

Key Qualifications

  • You are a clear and effective communicator, and enjoy collaborative problem solving
  • You enjoy working on a shared codebase that supports web-scale, mission critical applications; and the discipline that requires
  • You understand modern data engineering approaches, stay on top of developments, and are aware of what leading players are doing
  • You have a demonstrated ability to implement and extend highly performant, resilient, reliable, and understandable data pipelines
  • You have experience with Spark, Hadoop, HIVE, Kafka, Cassandra or other distributed systems
  • You have expertise in Python, Java, Scala, SQL, and/or other relevant languages and frameworks
  • You have experience with multiple machine learning libraries and frameworks such as tensor flow,
  • You have worked in cloud environments and are familiar with object stores, and other common cloud-native data storage and processing frameworks
  • You have worked in CI/CD environments
  • You have experience with pipelines and architectures that support machine learning development platforms and production applications
  • You are familiar with A/B and other online testing applications
  • You are familiar with statistics and are capable of using data analysis techniques to understand data quality, profile system loads, understand the relationships between business metrics, and technical performance


You will have the opportunity to define, refine, and/or refactor approaches, designs, and architectures to meet the ad network challenges we must solve. You will join a team of world-class machine learning engineers hungry to apply leading-edge technologies to deliver extraordinary experiences to our customers. You will play a meaningful role building products which deliver on Apple's privacy commitments and change the way advertising works with data. You will have the opportunity to improve and extend a platform with extreme scale requirements. You will have the chance to take part in designing and implementing the engineering solutions that brings cutting edge ad network algorithms into production in heterogeneous environments. You will apply cutting edge data engineering techniques, platform engineering techniques and algorithmic solutions. You will join and contribute to a culture that emphasizes observability and understandability, reliability, resiliency, simplicity, reusability, extensibility, scalability, velocity and productivity. We are one team, nurturing each other’s growth and supporting each other in delivering for our customers and Apple.

Education & Experience

BS/MS in Computer Science, Distributed Systems, Software Engineering, or related field; and experience designing, building, maintaining, and extending web-scale production systems.

Additional Requirements