Software Engineer - GenAI, Ai & Data Platforms (AiDP)

Apple•Sunnyvale, CA

About The Position

As a Software Engineer, you will design, develop, test, document, improve, and maintain code mostly in Java and Python (and other languages as needed) that will help build world class AI and Data platforms. You will partake in every aspect of your projects, from planning to design to implementation and future iterations, and you will be encouraged to play an extended role in designing solutions. The ideal candidate is self-motivated, pro-active and results-driven. Attention to detail, dedication to providing high-quality solutions modeling engineering excellence, and ability to work towards on-time delivery of projects are all crucial qualities needed to work at Apple as a Software Engineer. The ideal candidate will also possess excellent communication and collaboration skills to work with various internal and external partners.

Requirements

3+ years proven experience developing software in Java or Python in a professional capacity
2+ years proven experience implementing, and shipping high-scale, high-performance, highly available, fault-tolerant, and secure cloud-based distributed systems, including proficiency in API implementation (e.g. REST, RPC, GraphQL, etc.)
Demonstrated ability to conduct performance analysis and troubleshoot large scale distributed systems
Proficiency in data structures, algorithms, or software design patterns (e.g. GoF), with a proven focus on implementing testable, maintainable, and extensible backend code
BS in Computer Science, Computer Engineering, or a related technical field, or equivalent professional work experience

Nice To Haves

Experience with distributed orchestration, storage (Iceberg, Delta) & compute systems (e.g., Airflow, Spark, Flink, etc.)
Experience working with GenAI - building AI Agents, MCP servers, or Skills.
Proficiency in concurrency, memory management, and performance optimization techniques
Comfortable using CI/CD tools to build, test, deploy, and release containerized software applications on cloud-based Kubernetes (e.g. AWS EKS, GCP GKE, Azure AKS, etc.)