High-Performance Compute Engineer

20 hours ago


Delhi, Delhi, India BitOoda Full time
Job Overview:
As a Systems/Network Engineer, you will be responsible for architecting, deploying, and maintaining high-performance compute infrastructure leveraging NVIDIA GPUs. This role involves working on bare-metal systems, high-speed networks, and hybrid cloud integrations to ensure maximum performance, reliability, and scalability.

Key Responsibilities:
1. System Optimization: Configure and optimize bare-metal servers, including Linux OS, NVIDIA/AMD GPU drivers, and system libraries for peak performance.
2. GPU Cluster Management: Deploy and manage GPU clusters using job orchestration tools like Kubernetes, Slurm, or similar platforms, monitoring GPU utilization, thermals, and overall system health.
3. Networking: Design and maintain high-speed networking solutions (e.g., NVLink, InfiniBand, RDMA) for distributed GPU systems, optimizing data transfer between nodes and reducing latency in cluster communication.
4. Storage Solutions: Manage and configure storage solutions such as NVMe, SSD arrays, Ceph, or Lustre for high-throughput workloads, ensuring efficient storage management.
5. Automation: Automate system deployment, updates, and monitoring using tools like Ansible, Terraform, or Python scripts, enhancing efficiency and scalability.
6. Security: Implement secure access controls, firewalls, and VPNs to protect GPU resources and user data, ensuring compliance with security best practices for HPC environments.

Required Qualifications:
Technical Skills: Strong experience with Linux (CentOS, Ubuntu, RHEL), expertise in managing NVIDIA GPU ecosystems (CUDA, NVLink, NVIDIA drivers), familiarity with AMD ROCm, HIP, or OpenCL for AMD GPUs, knowledge of high-speed networking protocols (InfiniBand, RDMA, Ethernet), proficiency in scripting and automation (Python, Bash, Ansible, Terraform), experience with job orchestration tools like Kubernetes or Slurm, familiarity with containerization (Docker, NVIDIA Docker, Singularity), understanding of storage technologies, including NVMe and parallel file systems.

Compensation:
The estimated annual salary for this position is $120,000-$180,000, depending on experience.

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