Software Engineer, Apple Ads

Apple•Cupertino, CA

About The Position

Apple is where we use the power of technology to enrich people's lives. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something — you'll add something. Join the Apple Ads Engineering team and help build an advertising platform that benefits both customers and advertisers. Our technology makes advertising possible on the App Store, Apple News, Stocks, and Apple TV — helping people discover content, supporting creators and publishers, and connecting advertisers of all sizes with engaged audiences, all with the unwavering commitment to privacy you expect from Apple. In this role, you will design, develop, and launch the highly-performant, internet-scale backend systems that select and deliver the right ads in real time, collaborating across engineering, product, and infrastructure to bring elegant solutions into production at Apple scale.

Requirements

3+ years of industry experience architecting and developing internet-scale server software for Linux systems, including scalable micro-services or data-driven platforms.
Strong background in computer science fundamentals, including algorithms and data structures.
Strong coding skills in Go, Java, Rust, C++, Scala, or a similar OOP/Functional language.
Hands-on experience designing and operating scalable micro-services.
Experience with search technologies such as Lucene, Solr, or Elasticsearch.
Expertise with NoSQL datastores (e.g., Cassandra).
Proficiency with data processing technologies (e.g., Kafka, Spark, Flink) and methods for processing petabyte-scale datasets.
Experience with AWS services such as Amazon S3, EC2, and EKS/Kubernetes.
Strong problem-solving and debugging skills.
Demonstrated ability to work on complex problems and systems, alone or as part of a team, to deliver complete systems end to end.
Excellent written and verbal communication skills, with the ability to work effectively with technical and non-technical cross-functional teams, including operations and project management partners.
Bachelor's degree in Computer Science or equivalent experience.

Nice To Haves

Master's degree in Computer Science or a related field.
Experience creating groundbreaking technology for algorithmic search, machine learning, natural language processing, and artificial intelligence.
Experience building ad-serving, recommendation, or large-scale retrieval systems.
Familiarity with real-time bidding, candidate retrieval, or ranking pipelines.
Experience operating services with strict latency and availability SLOs.
Familiarity with privacy-preserving system design and data-handling practices.
Strong understanding of distributed systems fundamentals — consensus, replication, and fault tolerance.
A desire to work in a fast-paced and challenging environment, and a fast learner with strong motivation for growing and learning new technologies.

Responsibilities

Design, develop, and operate the distributed services that make real-time ad selection possible at Apple.
Architect and build low-latency, high-availability, high-throughput ad-serving systems in a cloud environment.
Engineer secure and scalable data processing pipelines that operate on petabyte-scale datasets.
Implement performant services that handle very high data volumes and QPS.
Work cross-functionally to ensure that optimal and correct ads are available for real-time selection, and that observability and flexibility are provided for stakeholders.
Contribute across a variety of backend systems, including opportunities to apply algorithmic search, machine learning, NLP, and AI to hard retrieval problems.
Write clean, efficient, well-documented code.
Participate in code reviews.
Mentor other engineers on the team.
Collaborate with internal partners across indexing, search, serving, operations, and program management to define requirements and deliver high-quality solutions.