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Nvidiaposted 5 months ago
$148,000 - $339,250/Yr
Full-time • Senior
Santa Clara, CA
Computer and Electronic Product Manufacturing
About the position
As a Senior AI-HPC Cluster Engineer at NVIDIA, you will lead the design and implementation of advanced GPU compute clusters that support demanding deep learning and high-performance computing workloads. This role involves addressing strategic challenges related to compute, networking, and storage design, while also focusing on effective resource utilization and evolving cloud strategies within a global computing environment.
Responsibilities
- 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 in running their workflows on clusters, including performance analysis and optimizations of deep learning workflows.
- Conducting root cause analysis and suggesting corrective actions for problems of 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 a variety of AI/HPC workloads.
- Working knowledge of cluster configuration management tools such as Ansible, Puppet, or Salt.
- Experience with AI/HPC advanced job schedulers, ideally familiar with Slurm, K8s, RTDA, or LSF.
- In-depth understanding of container technologies like Docker, Singularity, Shifter, or Charliecloud.
- Proficient in CentOS/RHEL and/or Ubuntu Linux distros, including Python programming and bash scripting.
- Experience with AI/HPC workflows that use MPI.
Nice-to-haves
- Experience with NVIDIA GPUs, CUDA Programming, NCCL, and MLPerf benchmarking.
- Experience with Machine Learning and Deep Learning concepts, algorithms, and models.
- Familiarity with InfiniBand with 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.
Benefits
- Highly competitive salaries
- Comprehensive benefits package
- Equity options
- Ongoing application acceptance
