NVIDIA
Senior AI and ML HPC Cluster Engineer
– NVIDIA
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. Make the choice to join us today!
Role Overview As a member of the GPU AI/HPC Infrastructure team, you will provide leadership in the design and implementation of groundbreaking 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 our GPU Compute Clusters, addressing compute, networking, 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.
What You’ll Be Doing
Provide leadership and strategic guidance on the management of large-scale HPC systems including deployment of compute, networking, and storage.
Develop and improve our ecosystem around GPU-accelerated computing, creating 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 needs.
Support researchers to run their workloads, including performance analysis and optimizations.
Conduct root‑cause analysis and suggest corrective action, proactively finding and fixing issues before they occur.
What We Need To See
Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience.
Minimum 5+ years designing and operating large‑scale compute infrastructure.
Experience with AI/HPC advanced job schedulers such as Slurm, K8s, PBS, 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.
Applied experience with AI/HPC workflows that use MPI.
Experience analyzing and tuning performance for AI/HPC workloads.
Passion for continual learning and staying ahead of emerging technologies in the HPC and AI/ML infrastructure fields.
Ways to Stand Out From the Crowd
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 such as PyTorch and TensorFlow.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is $136,000–$212,750 for Level 3, and $168,000–$264,500 for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 22, 2025.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Job ID: JR2006394
#J-18808-Ljbffr
– NVIDIA
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. Make the choice to join us today!
Role Overview As a member of the GPU AI/HPC Infrastructure team, you will provide leadership in the design and implementation of groundbreaking 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 our GPU Compute Clusters, addressing compute, networking, 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.
What You’ll Be Doing
Provide leadership and strategic guidance on the management of large-scale HPC systems including deployment of compute, networking, and storage.
Develop and improve our ecosystem around GPU-accelerated computing, creating 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 needs.
Support researchers to run their workloads, including performance analysis and optimizations.
Conduct root‑cause analysis and suggest corrective action, proactively finding and fixing issues before they occur.
What We Need To See
Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience.
Minimum 5+ years designing and operating large‑scale compute infrastructure.
Experience with AI/HPC advanced job schedulers such as Slurm, K8s, PBS, 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.
Applied experience with AI/HPC workflows that use MPI.
Experience analyzing and tuning performance for AI/HPC workloads.
Passion for continual learning and staying ahead of emerging technologies in the HPC and AI/ML infrastructure fields.
Ways to Stand Out From the Crowd
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 such as PyTorch and TensorFlow.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is $136,000–$212,750 for Level 3, and $168,000–$264,500 for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 22, 2025.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Job ID: JR2006394
#J-18808-Ljbffr