✦ Luna Orbit — AI & Machine Learning

Member of Technical Staff, ML Infra, AGI

at Amazon.com

📍 US, CA, San Francisco Unknown 💰 $150K – $150K USD / year Posted March 13, 2026
Salary $150K – $150K USD / year
Type Not Specified
Experience mid
Exp. Years Not specified
Education Not specified
Category AI & Machine Learning

This role involves building and maintaining AI research infrastructure at Amazon, focusing on GPU optimization, cloud infrastructure, and automation.

  • Design and maintain compute platform
  • Partner with research scientists
  • Implement security controls
  • Scale infrastructure with IaC
  • Optimize GPU performance

Environment includes AWS cloud services, Kubernetes orchestration, GPU pools, and infrastructure automation tools, supporting ML research and large-scale AI systems.

The ideal candidate is a mid-level cloud infrastructure engineer with experience in AWS, GPU optimization, and large-scale distributed systems. They possess strong skills in automation, security, and infrastructure as code, supporting AI research environments.

Experience with AWS and cloud infrastructureKnowledge of GPU optimizationExperience with Infrastructure as Code (IaC)Experience with KubernetesSecurity controls implementation
Experience with large-scale GPU poolsExperience with monitoring and automation solutionsExperience in ML infrastructureExperience with security standards
AWSAmazon Web ServicesAWS CDKKubernetes
AWSAmazon Web ServicesAWS CDKKubernetesGPUInfrastructure as CodeSecurity ControlsMonitoringAutomationDistributed Systems
AWSAmazon Web ServicesAWS CDKCloud InfrastructureKubernetesGPUGPU poolsInfrastructure as CodeSecurity ControlsMonitoringOrchestrationAutomationDistributed SystemsPerformance OptimizationGPU Architectures
collaborationproblem-solvingcreativitycommunicationteamworkadaptability
Industry Technology
Job Function Build and optimize AI research infrastructure
AWSAmazon Web ServicesAWS CDKKubernetesGPUGPU poolsInfrastructure as CodeSecurity ControlsMonitoringAutomationDistributed SystemsPerformance OptimizationGPU ArchitecturesML InfrastructureCloud Infrastructure

Lack of experience with AWS or cloud platforms, No GPU or infrastructure experience, No knowledge of Kubernetes, Lack of security controls experience

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