Cloud Infrastructure Engineer

The Synthetic Data Group (SDG) Cloud Infrastructure team at Apple is responsible for building the next generation of secure, high-performance cloud services to support machine learning/GenAI and synthetic data initiatives. We are a multi-functional team solving challenging engineering problems across distributed systems, large-scale data infrastructure, and cloud services.

Description

In this role, you will architect and develop the cloud infrastructure powering Apple's Machine Learning and Synthetic Data Platform. You will design scalable services and pipelines to process and manage large volumes of data, enabling cutting-edge ML applications. This role involves tackling complex distributed system challenges - from optimizing data storage and

retrieval to ensuring low-latency, high-throughput computations - all while maintaining world-class security and reliability. You will collaborate closely with machine learning engineers, data scientists, and other engineering teams to integrate new algorithms and data sources into our platform. Your work will involve full-stack ownership of cloud services: from defining system architecture and APIs to implementing back-end services and deploying infrastructure as code. We use a broad range of technologies including AWS services, Kubernetes, Terraform, Golang, and modern databases. We value simplicity and rigor: you will drive for clean, maintainable designs and use data-driven insights to continuously improve performance and scalability. You will also mentor other engineers and play a key role in setting technical direction. You'll have the opportunity to innovate - exploring alternative technologies, prototyping new solutions, and influencing product direction to better serve our internal customers. If you are excited by the prospect of building critical cloud infrastructure for AI/ML at a large scale, this role will allow you to do the best work of your life at Apple.","responsibilities":"Architect, build, and operate secure, scalable cloud infrastructure and services supporting ML and synthetic data platforms

Design and implement microservices and APIs, from system design through production deployment and operations

Build and optimize data storage, messaging, and service-to-service communication patterns for high throughput and low latency (e.g., S3, Postgres, SQS)

Develop and maintain Infrastructure-as-Code (Terraform, Helm Charts, Kubernetes Manifest) and automation for reliable, repeatable environments

Apply quantitative approaches (modeling, iterative prototyping, analysis, tooling) to optimize performance, cost, and reliability while meeting demanding experience goals

Drive cross-functional architecture alignment; influence partner teams and senior technical stakeholders through design reviews and technical proposals

Mentor engineers and establish engineering best practices for robustness, security , testing, and operational excellence