AIML - Sr Software Engineer, Machine Learning Platform Technologies

Weekly Hours : 40

Role Number : 200629100-0836

Summary

Are you an open-source contributor passionate about building the next generation of cloud-native ML infrastructure?

We're seeking a hands-on technical leader with deep expertise in Kubernetes, Crossplane, Golang / Rust, and agentic workflows to design and scale the platforms that power Apple's Siri, Search, and AI / ML ecosystems.

If you've contributed to CNCF projects such as Crossplane, ArgoCD, or Kubernetes, and you're driven to build infrastructure for ML training and inference—including optimizing for performance, cost, and automation—this role is for you. You'll architect at Apple scale, developing intelligent, declarative, and self-managing infrastructure that enables billions of seamless user experiences.

Description

Our MLPT Cloud Infrastructure Team within Apple's AI / ML organization designs, builds, and scales the foundational systems that power Siri, Search, and next-generation ML workloads. We're reimagining how infrastructure is managed—through agentic, event-driven workflows, Crossplane compositions, and self-healing control planes—to deliver Model Context Protocol (MCP)–based infrastructure servers that integrate seamlessly with ML and data workflows. You'll work closely with AI / ML engineers, SREs, and platform teams to deliver infrastructure that is automated, observable, and efficient across Apple-scale hybrid and multi-cloud environments.

Minimum Qualifications

BS / MS in Computer Science or related field (or equivalent practical experience).

5+ years of experience in distributed systems or cloud infrastructure engineering.

Strong programming experience in Golang and / or Rust; expertise in building controllers, operators, or automation systems.

Deep understanding of Kubernetes internals, controller-runtime, and Crossplane composition frameworks.

Experience with ArgoCD, Helm, and Infrastructure-as-Code (Terraform, Pulumi, or Crossplane).

Hands-on experience with GitOps, declarative configuration, and reconciliation-driven workflows.

Proven ability to design and operate infrastructure for ML training and inference, including performance tuning and GPU optimization.

Experience leading technical teams, driving architecture decisions, and mentoring engineers.

Strong grounding in cloud cost efficiency, performance profiling, and system-level debugging.

Preferred Qualifications

9+ years in cloud infrastructure, SRE, or distributed systems roles.

Active contributor to CNCF open-source projects (e.g., Kubernetes, Crossplane, ArgoCD, Envoy, Prometheus).

Deep expertise in Kubernetes API machinery, custom resources (CRDs), and control plane development.

Experience with Model Context Protocol (MCP)–based systems or contextual orchestration servers.

Familiarity with AIOps or agentic AI workflows in production environments.

Strong understanding of observability, telemetry, and distributed tracing (OpenTelemetry, Prometheus, Grafana).

Proven experience building ML infrastructure platforms (training clusters, inference services, model registries).

Excellent communication, technical writing, and cross-functional leadership skills.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant () .