As a Kubernetes AI Workload Engineer, you'll work closely with various teams to create a robust AI infrastructure. Your focus will be on deploying and managing AI workloads efficiently in a production environment.
Anicalls is looking for a Kubernetes AI Workload Engineer to join their team in Johannesburg. In this role, you will collaborate with business, data, and engineering teams to build a secure and scalable AI infrastructure. Your primary responsibility will be to design, deploy, and manage containerized AI and machine learning workloads on Kubernetes, ensuring they run smoothly in a production setting.
Your day-to-day tasks will involve working with various stakeholders to understand their needs and translating those into effective AI solutions. You will be responsible for the reliable scaling, scheduling, and resource management of AI workloads, which is crucial for the performance of machine learning applications. This role is ideal for someone who enjoys problem-solving and has a strong technical background in Kubernetes and AI technologies.
Key responsibilities include: • Designing and implementing containerized AI workloads • Managing Kubernetes clusters for optimal performance • Collaborating with cross-functional teams to ensure alignment on AI projects • Monitoring and troubleshooting AI applications in production
To succeed in this role, you should have a solid understanding of Kubernetes and experience with AI infrastructure. Familiarity with containerization and machine learning concepts is essential. If you are passionate about AI and enjoy working in a dynamic environment, this position could be a great fit for you.
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