HPC Engineer

Job: HPC Engineer

Rate: $50/hr C2C

Location: Remote Although the positions are remote for now, candidates must be aware if there are any changes from the client in the future than they may be asked to relocate to Redmond, WA.

LinkedIn : Must with photo location or match project

Also remember after offer candidate use own window 11 laptop

Summary

• We are seeking a highly skilled GPU Infrastructure Engineer to join our team. This role focuses on the design, implementation, and management of enterprise network and cloud-based infrastructure to support evolving Azure cloud needs. The ideal candidate will have a strong background in software, network, or systems engineering, along with hands-on experience in managing large-scale cloud and data center operations.

Responsibilities

• Respond to incidents during regular on-call rotations and resolve issues efficiently to minimize downtime.
• Design and plan scalable GPU infrastructure solutions to meet organizational capacity and performance needs.
• Collaborate with cross-functional teams to define and implement GPU infrastructure architecture that aligns with business objectives.
• Evaluate GPU technologies and recommend the best hardware and software configurations.
• Configure and deploy GPU servers, including installation and setup of hardware, software, and networking components.
• Coordinate with vendors for procurement and installation of GPUs and related infrastructure.
• Implement and manage GPU clustering setups for compute-intensive tasks.
• Utilize monitoring tools to assess GPU performance metrics and system health.
• Conduct benchmarking tests and analyze the results to identify performance bottlenecks.
• Optimize workload distribution across GPU resources to ensure maximum efficiency.
• Provide expert troubleshooting support for reporting and resolving GPU-related issues experienced by team members.
• Maintain incident response protocols to address hardware and software failures swiftly and effectively.
• Develop FAQs and knowledge base articles to streamline support processes for internal users.
• Infrastructure Maintenance:
• Schedule and perform routine maintenance, including updates to software, firmware, and drivers related to GPU systems.
• Plan and execute capacity upgrades and expansions as needed, ensuring minimal disruption to services.
• Conduct post-mortem analyses on significant incidents to improve overall system reliability.
• Write scripts for automation of deployment, configuration management, and system monitoring tasks (e.g., Python, Bash).
• Develop tools that increase productivity for engineering and data science teams using GPUs.
• Implement Infrastructure as Code (IaC) practices for efficient and repeatable deployments.

Requirement

• Bachelor’s or Master’s Degree in Computer Science, Information Technology, or a related field.

Technical Experience:

• Proven expertise in software engineering, network engineering, or systems administration.
• Hands-on experience with managing and debugging cloud backend server and networking infrastructure and services.
• Strong understanding of enterprise network and cloud-based architectures, including experience working with Cisco and Azure.
• Experience with cloud platforms providing GPU services (e.g., AWS, Google Cloud, Azure).
• Understanding virtualization technologies (e.g., Docker, Kubernetes) and server  orchestration tools.
• Knowledge of network configurations and storage solutions used in GPU environments.
• Strong understanding of GPU architectures (NVIDIA CUDA, AMD ROCm, etc.).
• Experience with AI/ML workloads, HPC, or rendering applications.
• Familiarity with PCIe, memory subsystems (DDR, HBM), and high-speed I/O.
• Understanding of Azure Pipeline , Azure DevOps.
• Demonstrated knowledge in deploying servers and network infrastructure equipment at scale.