Machine Learning & AI Infrastructure EngineerKORE1, a nationwide provider of staffing and recruiting solutions, has an immediate opening for a Machine Learning & AI Infrastructure Engineer that is fully remote. We are seeking a Machine Learning & AI Infrastructure Engineer to help design, deploy, and support advanced AI, machine learning, and high-performance computing (HPC) environments. This hands-on technical role will work directly with compute, storage, networking, and containerized infrastructure to deliver scalable, high-performance solutions for enterprise, healthcare, research, and academic organizations. The ideal candidate is passionate about AI infrastructure, thrives in complex technical environments, and enjoys solving challenging engineering problems while working alongside cross-functional teams. Key ResponsibilitiesDeploy, administer, and optimize AI and HPC infrastructure environments. Support compute, storage, networking, and container platforms across customer and internal environments. Troubleshoot system performance, reliability, and scalability issues. Assist with infrastructure automation and operational improvements. Collaborate with engineering teams to design and implement modern AI and machine learning platforms. Monitor and maintain infrastructure to ensure high availability and performance. Support customer implementations and ongoing operational needs. Required QualificationsStrong experience administering HPC bare-metal environments. Experience with NVIDIA Base Command Manager, Bright Cluster Manager, or similar HPC management platforms preferred. Hands-on Kubernetes administration experience, particularly with persistent storage provisioning and CSI integrations. Strong Linux administration skills, preferably Ubuntu. Experience with Bash and/or Python scripting. Strong troubleshooting and systems engineering capabilities. Preferred QualificationsExperience administering enterprise storage platforms such as Dell PowerScale/Isilon, VAST Storage, NetApp ONTAP, DDN IntelliFlash, or similar technologies. Experience with DDN Exascaler, Lustre, or other parallel file systems. Containerization and container orchestration experience. Familiarity with InfiniBand networking and NVIDIA UFM.Experience supporting enterprise Ethernet networking environments. Exposure to AI, machine learning, or GPU-accelerated computing environments. What Success Looks LikeReliable deployment and operation of AI and HPC environments. Strong system performance, scalability, and uptime. Effective collaboration with engineering and customer teams. Continuous improvement of infrastructure automation and operational processes. Successful delivery of complex technical solutions supporting advanced AI and research initiatives. Experience: 2 years required