Machine Learning Infrastructure Engineer (Associate or Experienced)

Machine Learning Infrastructure Engineer (Associate or Experienced)

Company:

The Boeing Company

The Boeing Company is seeking an Infrastructure Engineer (Entry Level or Associate) in Huntsville, AL.  This Infrastructure Engineer will support our Artificial Intelligence Innovation Lab infrastructure environments with an emphasis on Artificial Intelligence and Machine Learning (AI/ML) development platforms.

This position supports Linux and Windows systems, cloud and virtualization platforms, container orchestration technologies, and secure networking services. The selected candidate will work under general direction and collaborate with cross-functional teams including AI/ML engineers, DevOps, cybersecurity, and network engineering.

Boeing offers a comprehensive benefits package including generous Paid Time Off (PTO), flexible work environment, paid parental leave, Industry-leading retirement benefits with strong matching, very generous tuition assistance for earning advanced degrees, and paid medical leave programs.  For more information, click here.

Our teams are currently hiring for a broad range of experience levels including Entry-Level or Associate Level Software Engineers 

Position Responsibilities:

• Supports Linux and Windows system administration tasks including system monitoring, patching, updates, and routine maintenance
• Supports compliance with enterprise IT policies, cybersecurity standards, and regulatory requirements
• Assists with deployment and support of ML Ops tooling used to manage GPU computing resources for AI/ML workloads
• Supports management and operation of computing infrastructure used by AI and ML development teams
• Assists in configuring and maintaining network devices (firewalls, switches) to ensure secure and reliable operations
• Helps troubleshoot network connectivity issues, including VPN access, escalating complex issues to senior engineers as required
• Assists in optimizing cloud infrastructure resources to improve performance, cost efficiency, and scalability
• Supports virtualization platforms and cluster technologies, ensuring availability and performance
• Assists with administration of distributed storage and storage networking systems
• Supports Kubernetes cluster operations using platforms such as Rancher and OpenShift, ensuring cluster health and security
• Uses Kubernetes tooling to assist with containerized application deployment and orchestration
• Assists in administration of core network services, including DNS, DHCP, and LDAP across Linux and Windows environments
• Helps document infrastructure changes and asset data in Data Center Infrastructure Management (DCIM) and IP Address Management (IPAM) systems
• Assists with deployment and management of local generative AI models, supporting infrastructure optimization for AI workloads
• Collaborates with DevOps teams to develop, support, and troubleshoot CI/CD pipelines, primarily using GitLab
• Assists with automation of infrastructure provisioning and deployment workflows using scripting and infrastructure-as-code tools

Basic Qualifications (Required Skills / Experience):

• Bachelor’s degree
• Ability to obtain a U.S. Security Clearance for which the U.S. Government requires U.S. Citizenship
• 1+ years of experience with LINUX system administration
• 1+ years of experience developing software using Docker or Kubernetes for container-based applications
• 1+ years of experience with computing networking/storage concepts and architecture
   

Preferred Qualifications (Desired Skills / Experience):

• Bachelor of Science degree from an accredited course of study in engineering, engineering technology (including manufacturing engineering technology), chemistry, physics, mathematics, data science, or computer science and 2+ years of related work experience OR Bachelor’s Degree and 6+ years of directly related work experience OR 10+ years of related, relevant experience
• Ability to troubleshoot technical issues and communicate effectively with cross-functional teams
• Experience with cloud platforms such as AWS, Azure, or Google Cloud
• Experience supporting lab infrastructure environments
• Experience or exposure to virtualization technologies such as VMware, Hyper-V, Proxmox, or similar
• Basic experience with automation or scripting tools (Python, Bash, PowerShell, Ansible, Terraform, or similar)
• Familiarity with CI/CD concepts and tools, preferably GitLab
• Understanding of GPU compute concepts or high-performance workloads
• Experience working with Kubernetes clusters in production or lab environments
• Familiarity with distributed storage system