Machine Learning Infrastructure Engineer (associate or Experienced)

Boeing Boeing · Aerospace · Huntsville, AL

Boeing is hiring an Infrastructure Engineer to support their Artificial Intelligence Innovation Lab. The role involves supporting Linux and Windows systems, cloud and virtualization platforms, container orchestration (Kubernetes), secure networking, and ML Ops tooling. The engineer will assist with the deployment and optimization of infrastructure for AI/ML workloads, including generative AI models, and collaborate with DevOps teams on CI/CD pipelines.

What you'd actually do

  1. Supports Linux and Windows system administration tasks including system monitoring, patching, updates, and routine maintenance
  2. Supports compliance with enterprise IT policies, cybersecurity standards, and regulatory requirements
  3. Assists with deployment and support of ML Ops tooling used to manage GPU computing resources for AI/ML workloads
  4. Supports management and operation of computing infrastructure used by AI and ML development teams
  5. Assists in configuring and maintaining network devices (firewalls, switches) to ensure secure and reliable operations

Skills

Required

  • Bachelor's degree
  • LINUX system administration
  • Docker or Kubernetes for container-based applications
  • computing networking/storage concepts and architecture
  • Ability to obtain a U.S. Security Clearance

Nice to have

  • AWS, Azure, or Google Cloud
  • virtualization technologies
  • automation or scripting tools (Python, Bash, PowerShell, Ansible, Terraform, or similar)
  • CI/CD concepts and tools, preferably GitLab
  • GPU compute concepts or high-performance workloads
  • Kubernetes clusters in production or lab environments
  • distributed storage systems and storage networking
  • security best practices and compliance frameworks such as NIST
  • AI/ML or high-performance computing (HPC) environments
  • VPN and complex network connectivity issues
  • Active U.S. Secret Security Clearance

What the JD emphasized

  • AI/ML development platforms
  • AI/ML workloads
  • generative AI models
  • infrastructure optimization for AI workloads

Other signals

  • AI/ML development platforms
  • ML Ops tooling
  • GPU computing resources for AI/ML workloads
  • generative AI models
  • infrastructure optimization for AI workloads