Senior Infrastructure Software Engineer, GPU Clusters

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Job Overview

As a Senior Infrastructure Software Engineer focusing on GPU Clusters at NVIDIA, you will play a pivotal role in designing, deploying, and optimizing large-scale GPU computing systems. You will collaborate with cross-functional teams to enhance infrastructure performance and ensure robustness in diverse GPU workloads. Your expertise in software engineering and infrastructure management will contribute to advancing our technologies and supporting our clients’ intricate computational needs.

Job Responsibilities

• Design, implement, and maintain the architecture for large-scale GPU clusters.
• Collaborate with hardware teams to implement effective solutions for GPU integration.
• Develop automation tools and frameworks for provisioning and managing GPU resources.
• Optimize performance and efficiency of existing GPU workloads across various applications.
• Monitor and troubleshoot cluster performance issues, ensuring system reliability.
• Participate in code reviews and contribute to best practices for software development.
• Provide technical guidance and mentorship to junior engineers on the team.

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or a related field; a Master’s degree is preferred.
• 5+ years of experience in infrastructure software engineering, focusing on GPU or parallel computing.
• Proficiency in programming languages such as Python, C++, and Bash.
• Experience with orchestration tools like Kubernetes or Docker.
• Strong understanding of distributed computing systems and cloud architectures.
• Familiarity with performance tuning and profiling for GPU systems.
• Excellent problem-solving skills and ability to work in a fast-paced environment.

Technologies & Tools

This position will utilize a wide range of technologies and tools, including GPU programming frameworks such as CUDA and OpenCL, cloud services such as AWS and Azure for orchestrating GPU resources, virtualization tools like VMware, and configuration management software, including Ansible and Terraform. Familiarity with performance monitoring tools and cloud-native environments is essential to effectively manage and optimize GPU clusters.

Ideal Candidates

The ideal candidates for this position will possess a strong technical acumen, complemented by leadership capabilities and a teamwork-oriented mindset. They should demonstrate an eagerness to continuously learn and adapt to emerging technologies within the GPU computing space. Successful individuals will exhibit exceptional analytical and problem-solving skills, enabling them to tackle complex technical challenges effectively. A passion for innovation and ability to communicate complex ideas clearly is essential for collaboration with cross-functional teams.