Senior AI and ML HPC Cluster Engineer
NVIDIA · Illinois, United States
- Hybrid
- Full-time
- $200,000 / year
- Illinois, United States
Job highlights
- Lead design and implementation of GPU compute clusters.
- Develop scalable automation for GPU-accelerated computing.
- Build and maintain AI/ML heterogeneous clusters.
- Support researchers with performance analysis.
- Proactively identify and fix infrastructure issues.
About the role
Senior AI and ML HPC Cluster Engineer at 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!
About the Role
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 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.
What You'll Be Doing
- 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.
What We Need To See
- 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, 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 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.
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 IPoIB 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.
Compensation and Benefits
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits.
Application Details
Applications for this job will be accepted at least until April 28, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. 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. JR2016887
Key skills/competency
- AI/ML Infrastructure
- HPC Cluster Management
- GPU Compute Clusters
- System Administration (Linux)
- Automation Solutions
- Container Technologies
- Performance Analysis
- Networking
- Storage Systems
- Python Scripting
Skills & topics
- AI Engineer
- ML Engineer
- HPC Engineer
- Cluster Engineer
- Infrastructure Engineer
- GPU Computing
- Deep Learning
- High Performance Computing
- Linux System Administration
- Python Scripting
How to get hired
- Tailor your resume: Highlight experience with AI/HPC job schedulers, Linux administration, containerization, and Python scripting to match NVIDIA's requirements for a Senior AI and ML HPC Cluster Engineer.
- Showcase relevant projects: Detail your experience designing and operating large-scale compute infrastructure, especially with AI/ML workflows and performance tuning.
- Prepare for technical interviews: Be ready to discuss your knowledge of NVIDIA GPUs, CUDA, NCCL, MLPerf, InfiniBand, distributed storage, and deep learning frameworks.
- Demonstrate leadership and collaboration: Emphasize your ability to provide strategic guidance, cultivate relationships, and support diverse user needs in a complex technical environment.
- Understand NVIDIA's culture: Research NVIDIA's commitment to innovation, continuous learning, and diversity to align your answers with their values.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the key responsibilities for a Senior AI and ML HPC Cluster Engineer at NVIDIA?
- The Senior AI and ML HPC Cluster Engineer at NVIDIA will lead the design and implementation of GPU compute clusters, develop automation solutions for GPU-accelerated computing, build and maintain AI/ML heterogeneous clusters, support researchers with performance analysis, and proactively manage system issues. This role involves strategic guidance, customer and cross-team relationship building, and staying ahead of emerging technologies in HPC and AI/ML infrastructure.
- What technical skills are most important for this Senior AI and ML HPC Cluster Engineer role at NVIDIA?
- Essential technical skills for this role include a Bachelor's degree or equivalent experience, 5+ years in large-scale compute infrastructure design and operation, proficiency with AI/HPC job schedulers (Slurm, K8s, etc.), Linux administration (CentOS/RHEL, Ubuntu), cluster configuration tools (Ansible, Puppet, Salt), container technologies (Docker, Singularity), Python programming, bash scripting, and experience with MPI workflows and performance tuning for AI/HPC workloads.
- What experience would make a candidate stand out for the Senior AI and ML HPC Cluster Engineer position at NVIDIA?
- Candidates who stand out will have background experience with NVIDIA GPUs, CUDA Programming, NCCL, and MLPerf benchmarking. Familiarity with Machine Learning and Deep Learning concepts, algorithms, and models, as well as knowledge of InfiniBand and fast, distributed storage systems like Lustre and GPFS, will be highly advantageous. Experience with deep learning frameworks like PyTorch and TensorFlow is also a plus.
- What is the typical salary range for a Senior AI and ML HPC Cluster Engineer at NVIDIA?
- The base salary for this role varies by level. For Level 3, the range is 152,000 USD to 241,500 USD. For Level 4, the range is 184,000 USD to 287,500 USD. This is in addition to potential equity and benefits.
- Does NVIDIA use AI in its recruiting process for the Senior AI and ML HPC Cluster Engineer role?
- Yes, NVIDIA utilizes AI tools in its recruiting processes, including for roles like the Senior AI and ML HPC Cluster Engineer. This may involve AI-powered resume screening or other assessment tools to identify suitable candidates.
- How can I best prepare my resume for the Senior AI and ML HPC Cluster Engineer application at NVIDIA?
- To best prepare your resume for the Senior AI and ML HPC Cluster Engineer role at NVIDIA, clearly highlight your 5+ years of experience in designing and operating large-scale compute infrastructure. Emphasize your expertise with AI/HPC schedulers, Linux distributions, container technologies, automation tools, Python, and MPI. Quantify your achievements in performance analysis and optimization wherever possible.
- What are NVIDIA's diversity and inclusion policies relevant to the Senior AI and ML HPC Cluster Engineer position?
- NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. They do not discriminate in hiring or promotion practices based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. This commitment to diversity is highly valued in their current and future employees.