Senior AI-HPC EDA Cluster Engineer

NVIDIA • Redmond, WA

99d • $148,000 - $235,750

About The Position

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are seeking a highly skilled and experienced AI-HPC Cluster Engineer to design, deploy, and operate GPU Compute Clusters for EDA and high-performance computing workloads used across multiple teams and projects. Join our engineering team and collaborate with researchers and infrastructure teams to ensure our GPU clusters perform efficiently, scale well, and remain reliable.

Requirements

• Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience.
• Minimum of 5 years of proven experience crafting and operating large scale compute infrastructure, including cluster configuration managements tools such as BCM or Ansible.
• Experience with AI/HPC job schedulers and orchestrators, such as Slurm, LSF, PBS or K8s.
• Applied experience with AI/HPC workflows that use MPI and NCCL.
• Proficient in using Linux including Rocky/Centos/RHEL and/or Ubuntu Linux distributions.
• A solid understanding of container technologies such Enroot and Docker.
• Proficiency in one scripting language (Python, Bash) and at least one compiled language (Golang, Rust, C, C++...).
• Experience analyzing and tuning performance for a variety of AI/HPC workloads.
• Excellent problem-solving to analyze complex systems, identify bottlenecks, and implement scalable solutions.
• Excellent communication and collaboration skills, with the ability to work effectively with various teams and individuals.
• Passion for continual learning and staying ahead of new technologies and effective approaches in the HPC infrastructure fields.

Nice To Haves

• Background with NVIDIA GPUs, CUDA Programming, NCCL and MLPerf benchmarking.
• Experience supporting EDA workloads and tools.
• Familiarity with High-Speed Networking pertaining to HPC including InfiniBand, RDMA and RoCE.
• Understanding of fast, distributed storage systems such as Lustre and GPFS for AI/HPC workload.
• Familiarity with metrics collection and visualization at scale with Prometheus, OpenSearch and Grafana.

Responsibilities

• Provide leadership and strategic mentorship 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.
• Continuously improve infrastructure provisioning, management, observability and day to day operation through automation.
• Build and nurture customer and cross-team relationships to consistently support the clusters and address changing 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.
• Build innovative tooling to accelerate researchers' velocity, debugging and software performance at scale.

Benefits

• Competitive salaries
• Equity
• Benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Bachelor's degree
• Number of Employees: 5,001-10,000 employees