Are you an open-source contributor passionate about building the next generation of cloud-native ML infrastructure? We're looking for a hands-on technical leader with deep expertise in Kubernetes, Crossplane, Golang/Python, and agentic workflows to design and scale the platforms that power Apple's Search and ML infrastructure ecosystems. If you've contributed to CNCF projects such as Kubernetes, Crossplane, or ArgoCD-and you're driven to build intelligent, automated infrastructure for ML training and inference at massive scale-this role is for you. You'll architect systems that are declarative, self-managing, and highly performant, enabling seamless ML experiences for billions of users.
The AI, Search & Knowledge Platform Cloud Infrastructure Team within Apple's Services organization designs, builds, and scales the foundational systems that power Search, and next-generation machine learning workloads. We are reimagining how infrastructure is managed through agentic, event-driven workflows, Crossplane compositions, and self-healing control planes. You'll develop Model Context Protocol (MCP)-based infrastructure servers that integrate with ML and data workflows, delivering highly automated and observable infrastructure across hybrid and multi-cloud environments.\nYou will collaborate across ML engineering, SRE, and platform teams to deliver infrastructure that adapts intelligently to application needs, optimizes for cost and performance, and accelerates the development of ML training and inference pipelines.
BS/MS in Computer Science or equivalent practical experience.\n5+ years of experience in leading distributed systems or cloud infrastructure engineering.\nStrong programming experience in Golang and Python, including building controllers, operators, or automation systems.\nDeep understanding of Kubernetes internals, controller-runtime, and Crossplane composition frameworks.\nExperience with ArgoCD, Helm, and IaC (Terraform or Crossplane).\nHands-on experience with GitOps and reconciliation-driven workflows.\nProven ability to design and operate infrastructure for ML training and inference, including performance tuning and GPU optimization.\nExperience leading technical teams and driving architectural decisions.\nStrong grounding in cost efficiency, performance profiling, and system-level debugging.
9+ years in cloud infrastructure, SRE, or distributed systems roles.\nContributions to CNCF open-source projects (Kubernetes, Crossplane, ArgoCD, Envoy, Prometheus, etc.).\nDeep expertise in Kubernetes API machinery, CRDs, and control plane development.\nExperience with Model Context Protocol (MCP) or contextual infrastructure servers.\nFamiliarity with AIOps or agentic/LLM-driven automation in production environments.\nStrong understanding of observability and distributed tracing (OpenTelemetry, Prometheus, Grafana).\nExperience building ML infrastructure platforms (training clusters, inference systems, model registries).\nExcellent communication, cross-functional leadership, and technical writing skills.\nB.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or equivalent practical experience is preferred
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90733111
- Position Id: 2dbc41e8711c5a089d11d3819b50371a
- Posted 4 hours ago
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