Senior AI-HPC Cluster Engineer

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a "learning machine" that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world.

As a Senior AI-HPC Cluster Engineer, you will be a member of the GPU AI/HPC Infrastructure team, providing leadership in the design and implementation of ground breaking GPU compute clusters that run demanding deep learning, high performance computing, and computationally intensive workloads. You will help identify architectural changes and new approaches for GPU Compute Clusters, addressing strategic challenges such as compute, networking, and storage design for large scale, high performance workloads, effective resource utilization in a heterogeneous compute environment, evolving private/public cloud strategy, capacity modeling, and growth planning across the global computing environment.

Key responsibilities include:

• Building and improving the ecosystem around GPU-accelerated computing, including developing large scale automation solutions
• Maintaining and building deep learning clusters at scale
• Supporting researchers to run their workflows on clusters, including performance analysis and optimizations of deep learning workflows
• Conducting root cause analysis and suggesting corrective actions for problems at various scales
• Proactively finding and fixing problems before they occur

Requirements:

• Bachelor's degree in Computer Science, Electrical Engineering or related field (or equivalent experience)
• Minimum 5 years of experience designing and operating large scale compute infrastructure
• Experience analyzing and tuning performance for various AI/HPC workloads
• Working knowledge of cluster configuration management tools (e.g., Ansible, Puppet, Salt)
• Experience with AI/HPC advanced job schedulers (e.g., Slurm, K8s, RTDA, LSF)
• In-depth understanding of container technologies (Docker, Singularity, Shifter, Charliecloud)
• Proficiency in CentOS/RHEL and/or Ubuntu Linux distros, including Python programming and bash scripting
• Experience with AI/HPC workflows using MPI

Preferred qualifications:

• Experience with NVIDIA GPUs, CUDA Programming, NCCL, and MLPerf benchmarking
• Familiarity with Machine Learning and Deep Learning concepts, algorithms, and models
• Experience with InfiniBand, IBOP, and RDMA
• Understanding of fast, distributed storage systems like Lustre and GPFS for AI/HPC workloads
• Familiarity with deep learning frameworks like PyTorch and TensorFlow

NVIDIA offers competitive salaries, comprehensive benefits, and the opportunity to work with some of the most brilliant and talented people in the world. Join us in our mission to amplify human imagination and intelligence.