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.