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.

Description:

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.

You 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.","responsibilities":"Architect and develop cloud-native, agentic infrastructure platforms supporting ML training, inference, and large-scale distributed systems.

Lead and mentor engineers building Crossplane-based control planes, Kubernetes operators, and ArgoCD-driven Git Ops automation.

Design, implement, and optimize MCP-based infrastructure servers that contextualize and manage infrastructure and application state across environments.

Contribute to CNCF open-source projects and represent Apple in the cloud-native community.

Implement observability, governance, and automation frameworks to ensure performance, reliability, security, and compliance.

Integrate agentic orchestration workflows for self-service provisioning, ML pipeline management, and dynamic infrastructure scaling.

Drive best practices for Git Ops, Infrastructure-as-Code, and Kubernetes cluster lifecycle automation at global scale.

Ensure systems are resilient, cost-efficient, and optimized for performance across on-prem and multi-cloud environments.

Preferred Qualifications:

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

Contributions to CNCF open-source projects (Kubernetes, Crossplane, ArgoCD, Envoy, Prometheus, etc.).

Deep expertise in Kubernetes API machinery, CRDs, and control plane development.

Experience with Model Context Protocol (MCP) or contextual infrastructure servers.

Familiarity with AIOps or agentic/LLM-driven automation in production environments.

Strong understanding of observability and distributed tracing (Open Telemetry, Prometheus, Grafana).

Experience building ML infrastructure platforms (training clusters, inference systems, model registries).

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

B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or equivalent practical experience is preferred

Minimum Qualifications:

BS/MS in Computer Science or equivalent practical experience.

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

Strong programming experience in Golang and Python, including building controllers, operators, or automation systems.

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

Experience with ArgoCD, Helm, and IaC (Terraform or Crossplane).

Hands-on experience with Git Ops 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 and driving architectural decisions.

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

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 .

Pay & Benefits:

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.