Senior DevOps Engineer

Responsibilities

• Design, build, and maintain scalable infrastructure to support the AI Workbench Platform and its underlying domain foundation models
• Implement and manage Kubernetes clusters with multi-GPU scheduling capabilities to support large-scale model training and inference workloads
• Develop and maintain Infrastructure as Code using Terraform to provision cloud resources reliably and reproducibly Package, deploy, and manage applications using Helm and Kustomize across multiple environments
• Collaborate with data scientists, ML engineers, and business units to enable seamless model consumption and fine-tuning workflows at scale Ensure platform reliability, scalability, and security for both internal teams and external customers Optimize resource utilization and cost efficiency across GPU-intensive…
• Monitor system performance and troubleshoot production issues to maintain high availability
• Contribute to platform architecture decisions and best practices for MLOps at enterprise scale

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