Jubil ID: 57

Company: Google

Location: San Francisco, CA

Description:
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 sol

Qualifications:
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 with AI/HPC advanced job schedulers
such as Slurm
K8s
RTDA or LSF Proficient in administering Centos/RHEL and/or Ubuntu Linux distributions Solid understanding of cluster configuration managements tools such as Ansible
Puppet
Salt In depth understating of container technologies like Docker
Singularity
Podman
Shifter
Charliecloud Proficiency in Python programming and bash scripting Excellent problem-solving skills
with the ability to analyze complex systems
identify bottlenecks
and implement scalable solutions Applied experience with AI/HPC workflows that use MPI Excellent communication and teamwork skills
with the ability to work effectively with diverse teams and individuals Experience analyzing and tuning performance for a variety of AI/HPC workloads Passion for continual learning and staying ahead of emerging technologies and effective approaches in the HPC and AI/ML infrastructure fields 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:
NVIDIA offers highly competitive salaries and a comprehensive benefits package Your base salary will be determined based on your location
experience
and the pay of employees in similar positions You will also be eligible for equity and benefits

Responsibilities:
We seek a technical leader 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 Provide leadership and strategic guidance on the management of large-scale HPC systems including the deployment of compute
networking
and storage Develop and improve our ecosystem around GPU-accelerated computing including developing scalable automation solutions Build and maintain AI and ML heterogeneous clusters on-premises and in the cloud Create and cultivate customer and cross-team relationships to reliably sustain the clusters and meet user evolving user needs Support our researchers to run their workloads including performance analysis and optimizations Conduct root cause analysis and suggest corrective action Proactively find and fix issues before they occur