Join Anicalls as a Kubernetes AI Workload Engineer, where you'll work with diverse teams to create robust AI infrastructure. This role is perfect for those passionate about deploying and managing AI workloads in a production environment.
As a Kubernetes AI Workload Engineer at Anicalls, you will play a crucial role in building and managing AI infrastructure that supports machine learning applications. Your primary focus will be on designing, deploying, and maintaining containerized workloads on Kubernetes, ensuring they are secure, scalable, and efficient. This position requires collaboration with various teams, including business, data, and engineering, to deliver high-quality solutions that meet production demands.
In your day-to-day work, you will: • Design and implement containerized AI workloads using Kubernetes. • Ensure reliable scaling and scheduling of resources for machine learning applications. • Collaborate with cross-functional teams to align on project goals and requirements.
This role is ideal for individuals who have a strong background in Kubernetes and AI infrastructure. You should be comfortable working in a fast-paced environment and have a passion for deploying innovative solutions. If you have experience with Generative AI and resource management, that's a plus, but not mandatory. Your ability to work collaboratively and focus on security will be key to your success in this position.
You'll be taken to the original listing on PNet to apply.