Nvidia Senior AI-HPC Cluster Engineer 

United States, Texas 

698481483

As a member of the GPU AI/HPC Infrastructure team, you will provide leadership in the design and implementation of ground breaking GPU compute clusters that run demanding deep learning, high performance computing, and computationally intensive workloads. We seek an expert to identify architectural changes and/or completely new approaches for our GPU Compute Clusters. As an expert, you will help us with the strategic challenges we encounter including: compute, networking, and storage design for large scale, high performance workloads, effective resource utilization in a heterogeneous compute environment, evolving our private/public cloud strategy, capacity modeling, and growth planning across our global computing environment.

• Building and improving our ecosystem around GPU-accelerated computing including developing large scale automation solutions

• Maintaining and building deep learning clusters at scale

• Supporting our researchers to run their flows on our clusters including performance analysis and optimizations of deep learning workflows

• Root cause analysis and suggest corrective action for problems large and small scales

• Finding and fixing problems before they occur

• 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 managements tools such as Ansible, Puppet, Salt.

• Experience with AI/HPC advanced job schedulers, and ideally familiarity with schedulers such as Slurm, K8s, RTDA or LSF

• In depth understating of container technologies like Docker, Singularity, Shifter, Charliecloud

• Proficient in Centos/RHEL and/or Ubuntu Linux distros including Python programming and bash scripting

• Experience with AI/HPC workflows that use MPI

• 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