Senior AI-HPC EDA Cluster Engineer at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, AI, SemiconductorsIndustries

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 management 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 as 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

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

Skills

Key technologies and capabilities for this role

GPUHPCEDACluster EngineeringAutomationNetworkingStorageObservabilityPerformance AnalysisRoot Cause Analysis

Questions & Answers

Common questions about this position

What experience level is required for this Senior AI-HPC EDA Cluster Engineer role?

A minimum of 5 years of proven experience crafting and operating large scale compute infrastructure is required, along with a Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience.

What key technical skills are needed for this position?

Required skills include experience with cluster configuration tools like BCM or Ansible, AI/HPC job schedulers such as Slurm, LSF, PBS or K8s, proficiency in Linux distributions like Rocky/Centos/RHEL or Ubuntu, container technologies like Enroot and Docker, and scripting in Python/Bash plus a compiled language like Golang, Rust, C, or C++.

What is the salary or compensation for this role?

This information is not specified in the job description.

Is this a remote position, or what is the location policy?

This information is not specified in the job description.

What does NVIDIA's company culture look like for this team?

NVIDIA offers a diverse, supportive environment where everyone is inspired to do their best work, with opportunities to collaborate with researchers and infrastructure teams while building cross-team relationships.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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