Senior ML Infrastructure SRE

Apple and help us leave the world better than we found it. 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.

Software and Systems Engineer to join our dynamic team.

About Apple

• At Apple, we don’t just build products — we create transformative experiences that have reshaped entire industries.
• Our innovation is driven by the diversity of our people and their ideas, inspiring everything we do.
• Imagine the impact you could make.
• 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.

Requirements

• This role demands a proactive mindset, technical excellence, and a collaborative spirit.
• 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
• 5+ 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

• 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