Cloud Engineer 3

Cullerton Group has a new opportunity for a Cloud Engineer 3. The work will be done onsite or hybrid depending on the customer’s preference. This is a long-term position that can lead to permanent employment with our client. Compensation is $86.09/hr + full benefits (vision, dental, health insurance, 401k, and holiday pay). Job Summary We are seeking a highly skilled Senior Server Administrator to join an AI Engineering team supporting high-performance computing infrastructure. The engineer will be responsible for deploying, maintaining, and optimizing NVIDIA GPU-based systems that enable advanced AI and machine learning workloads. This role involves close collaboration with data scientists, DevOps engineers, and software developers to ensure systems are reliable, scalable, and tuned for maximum performance. Key Responsibilities • Administer and maintain GPU-accelerated servers and clusters, including NVIDIA A100, H100, and other advanced GPUs. • Manage and optimize NVIDIA software stack components such as CUDA, cuDNN, TensorRT, NCCL, and NGC containers. • Monitor system performance, troubleshoot hardware and software issues, and ensure high availability of AI infrastructure. • Collaborate with DevOps and AI teams to support containerized workflows (Docker, Kubernetes) and distributed training environments. • Implement security best practices, lifecycle management, and documentation for GPU servers and infrastructure. Required Qualifications • Bachelor’s degree in Computer Science, Information Systems, or related field. • 8+ years of experience in IT infrastructure, including 5+ years of server administration. • Minimum of 3 years working with NVIDIA GPU-based systems. • Proficiency in Linux system administration, HPC, or AI environments. • Experience with NVIDIA GPU drivers, CUDA toolkit, and performance tuning. • Familiarity with Slurm, Kubernetes, Prometheus, Grafana, Ansible, or Terraform. • Strong scripting skills (Bash, Python). • Excellent communication and problem-solving abilities. Preferred Qualifications • NVIDIA Certified Professional or similar credentials. • Experience with multi-GPU and multi-node environments. • Familiarity with AI/ML frameworks (TensorFlow, PyTorch) and their GPU dependencies. • Experience with cloud-based GPU infrastructure (AWS, Azure, GCP). • Prior experience supporting high-performance computing or AI platforms. Why This Role? This position offers the opportunity to work on cutting-edge AI infrastructure supporting large-scale GPU environments and high-performance systems. You’ll collaborate with a forward-thinking engineering team driving the development of advanced data and compute technologies. Cullerton Group provides a professional environment with growth potential and long-term partnership opportunities with top-tier clients.