Cloud Infrastructure Engineer

Summary

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.

About the role

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
• Participate in Agile development workflows and contribute to continuous improvement across planning, execution, and delivery

Minimum Qualifications

• BS and a minimum of 10 years relevant industry experience
• 5+ years of software engineering experience building and operating cloud infrastructure or distributed systems at scale
• Hands-on experience with AWS services including EC2, EKS, S3, ELB and SQS
• Experience with Kubernetes-based container orchestration and production operations
• Proficiency with Infrastructure-as-Code tools such as Terraform
• Strong programming skills in Go (Golang) for systems and service development
• Proficiency in at least one additional language used for full-stack services development (JavaScript, Python)
• Experience designing and building microservices-based architectures in production
• Experience with relational databases (e.g., Postgres) and NoSQL datastores in production environments
• Demonstrated ability to use a quantitative approach to architect and develop robust, secure, high-performance cloud services (modeling, iterative prototyping, analysis, tools)
• Track record of influencing cross-functional architects and high-performance teams to define architecture
• Exposure to Agile development methodologies

Preferred Qualifications

• Experience designing and building applications using container and serverless technologies
• Good exposure to Agile software development and DevOps practices such as Infrastructure as Code (IaC), Continuous Integration, and automated deployment

• Experience with CI tools (e.g., Jenkins)
• Strong practical application development experience on Linux systems
• Excellent communication and collaboration skills
• Experience with film and game development pipelines (plus)