Description
The Senior MLOps Solutions Engineer will architect and build high-scale, enterprise-grade AI/ML solutions by integrating Pure Storage platforms with open-source MLOps tools such as Kubeflow, MLflow, and Ray. The role covers end-to-end MLOps pipeline automation, GPU-accelerated Kubernetes infrastructure, high-throughput model serving, distributed training, and technical enablement for sales and partners. Candidates need deep Python and deep-learning expertise, GPU and Kubernetes knowledge, and experience with infrastructure-as-code and high-performance data center infrastructure. The position is primarily in-office at an unspecified office location.
