Senior AI-HPC Cluster Engineer

Nvidia

Santa Clara, CA

Full Time

Senior

184k-357k

16 days ago

Job Description

About the Role

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. This is our life's work, to amplify human imagination and intelligence. 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.

Key Responsibilities

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 needs.
Support researchers in running workloads including performance analysis and optimizations.
Conduct root cause analysis and suggest corrective actions.
Proactively find and fix issues before they occur.

Requirements

Bachelor's degree in Computer Science, Electrical Engineering or related field or equivalent experience.
Minimum 8 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 management tools such as Ansible, Puppet, Salt.
In-depth understanding 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 AI/HPC workloads.
Passion for continual learning and staying ahead of emerging technologies in HPC and AI/ML infrastructure.

Nice to Have

Background 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.

Qualifications

Educational background with a Bachelor's degree in relevant fields or equivalent experience.
At least 8 years of experience in large-scale compute infrastructure design and operation.

Benefits & Perks

Highly competitive salaries.
Comprehensive benefits package.
Eligibility for equity and benefits.
Base salary range from 184,000 USD to 356,500 USD, determined by location, experience, and similar roles.

Working at Nvidia

NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most brilliant and talented people in the world working for us and, due to unprecedented growth, our world-class engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer, valuing diversity in our current and future employees.

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