ML Infrastructure Service Reliability Engineer- Apple Services Engineering

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The ML Infrastructure team is responsible for managing Apple’s largest ML compute platform, multi-cloud storage abstraction and caching platform, which supports critical machine learning training workloads that power user-facing features across the Apple ecosystem. Operating across both first-party and third-party cloud environments brings complex and unique challenges.

As a Site Reliability Engineer (SRE) on the ML Infrastructure team, you’ll be expected to address these challenges through a strong foundation in cloud object storage, data analysis, automation, collaboration, and advanced expertise in Kubernetes. Our team oversees the full infrastructure stack — from low-level nodes to the complete network architecture — ensuring our platform remains highly available, resilient, and efficient at scale.

Description

• We are seeking an experienced Software and Systems Engineer to join our dynamic team. This role demands a proactive mindset, technical excellence, and a collaborative spirit.
• The ideal candidate will demonstrate:
• Strong critical thinking and a high degree of individual accountability
• Effective communication and collaboration skills
• A genuine passion for Infrastructure as a Service (IaaS)
• A commitment to automation and operational efficiency
• Ownership of projects from design through delivery
• A solutions-oriented approach, coupled with the ability to gain alignment on
• technical direction
• Consistent and timely execution of design implementations aligned with
• project objectives
• The ability to provide constructive technical feedback, fostering team-wide
• growth and continuous improvement

Minimum qualifications

• 4+ years experience in building, operating and scaling a large application in a private, public or hybrid cloud environment
• Deep expertise in Kubernetes, with hands-on experience using platforms such as Google Kubernetes Engine (GKE) or Amazon Elastic Kubernetes Service (EKS)
• Proficient in designing, developing, and releasing code in languages such as Python, Go, or Rust
• Practical experience with object storage technologies, including Amazon S3 or Google Cloud Storage (GCS)
• Strong background in designing and troubleshooting complex networking issues in both public and private cloud infrastructures
• Solid understanding of Linux internals, standard networking protocols, and distributed systems architecture

Preferred qualifications

• Proven drive to automate manual operations and enhance processes through continuous iteration
• Strong understanding of best practices for deploying large-scale, distributed applications
• Hands-on experience managing diverse system environments using configuration management tools or software delivery platforms such as Spinnaker, Helm, or Flux
• Demonstrated expertise in deploying, supporting, and monitoring both new and existing services, platforms, and application stacks
• Solid familiarity with container orchestration and management using Kubernetes