Senior Infrastructure Software Engineer at NVIDIA

Shanghai, China

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

Requirements

BS or higher degree in computer science with 4+ years of relevant experience
Adept programming skills in multiple languages including Python
In-depth experience with distributed systems and cluster management stacks (logging, monitoring, scheduling, etc.)
Hands-on experience with continuous integration and deployment tools (e.g. GitlabCI)
Outstanding ability to understand users, prioritize among many contending requests, and build consensus
Passion for “it just works” automation, eliminating repetitive tasks, and enabling team members
Deep understanding of Linux system administration and container technologies
Proficient English communication skills

Responsibilities

Architect, develop, and maintain Python-based tools and services to efficiently run a performance-focused multi-tenant Linux cluster including embedded, desktop, and server systems
Work with industry standard tools (Kubernetes, Slurm, Ansible, Gitlab, Artifactory, Jira)
Actively support users doing development, functional testing, and performance testing on current and pre-production GPU cluster systems
Work with various teams at NVIDIA across different timezones to incorporate and influence the latest tools for operating GPU clusters
Collaborate with users and system administrators to seek out ways to improve UX and operational efficiency
Become an expert on the entire AI infrastructure stack

Skills

Key technologies and capabilities for this role

PythonKubernetesSlurmAnsibleGitlabArtifactoryJiraLinux

Questions & Answers

Common questions about this position

What education and experience are required for this Senior Infrastructure Software Engineer role?

A BS or higher degree in computer science with 4+ years of relevant experience is required, along with adept programming skills in multiple languages including Python.

What key technical skills are needed for this position?

Candidates need in-depth experience with distributed systems and cluster management stacks, hands-on experience with continuous integration tools like GitlabCI, deep understanding of Linux system administration and container technologies, and proficiency with tools like Kubernetes, Slurm, and Ansible.

Is this a remote position, or is there a location requirement?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What makes a candidate stand out for this NVIDIA position?

Stand out with experience automating bare-metal clusters, GPU computing systems, a track record of incorporating new technologies into development flows, or contributions as a maintainer to open-source software projects.

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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