MLOps / DevOps Engineer (Kubernetes/GPU Specialist) Rate: £550 Outside IR35 Arrangement: 2x a Month On-Site Duration: ASAP Start - 6 Month Contract We are seeking a highly skilled and motivated DevOps Engineer to join our team, focusing on the integration and optimization of network-intensive application components and software pipelines within virtualized environments. The ideal candidate will have strong hands-on experience with containerization technologies, including Kubernetes and Docker, and will be responsible for managing complex workloads that require high data throughput, GPU/NIC virtualization, and efficient network optimization. Key Responsibilities: Integrate network-intensive application components and software pipelines into virtualized environments such as Kubernetes and OpenStack. Implement and manage Kubernetes volumes, ensuring high availability, security, and scalability. Oversee Kubernetes GPU and NIC virtualization, optimizing resources for high-performance workloads. Deploy and manage containerized applications using Docker and Kubernetes. Collaborate with development teams to support AI and ML workloads, ensuring proper resource allocation and performance tuning. Handle scenarios with high data load, optimizing network throughput to enhance performance and efficiency. Continuously monitor and improve system performance, reliability, and scalability. Work closely with cross-functional teams to articulate technical concepts clearly and concisely. Key Requirements: Strong hands-on experience with containerization technologies, specifically Kubernetes and Docker. Familiarity with virtualized environments such as Kubernetes and OpenStack. Experience in implementing and managing Kubernetes volumes, GPU, and NIC virtualization. Basic understanding of AI and ML workloads, with the ability to support and optimize relevant applications. Demonstrated ability to manage high data load scenarios and optimize network throughput. Excellent communication skills, with the ability to explain technical concepts clearly to both technical and non-technical stakeholders. Familiarity with network and system performance tuning in virtualized and containerized environments. Preferred Qualifications: Experience with OpenStack or other cloud infrastructure platforms. Familiarity with infrastructure-as-code (IaC) tools such as Terraform or Ansible. Certification in Kubernetes (CKA, CKAD) or other relevant cloud technologies.