GPU Setup Engineer AI/Cloud Infrastructure

Key Responsibilities

• Deploy, configure, and maintain GPU-based AI/ML infrastructure
• Work hands-on with NVIDIA GPUs, CUDA, GPU drivers, and GPU compute environments
• Troubleshoot GPU performance, utilization, memory, and compute issues
• Support AI/ML workloads across cloud and on-premise environments
• Work with Docker and Kubernetes for containerized GPU workloads
• Optimize GPU resource utilization and workload performance
• Monitor GPU infrastructure health, capacity, and performance
• Collaborate closely with AI/ML, DevOps, and infrastructure teams

Required Skills:

• 6+ years of relevant experience
• Strong hands-on experience with NVIDIA GPUs and CUDA
• Linux administration and troubleshooting
• Docker and Kubernetes
• GPU infrastructure deployment and troubleshooting
• Experience with AWS, Azure, or GCP
• Python and/or Bash scripting
• GPU monitoring and performance optimization
• Experience supporting production AI/ML infrastructure

Good to Have:

• NVIDIA GPU cluster experience
• Kubernetes GPU scheduling
• NVIDIA Container Toolkit
• Slurm or other GPU workload schedulers
• MLOps / AI infrastructure experience
• Large-scale GPU cluster experience