Senior Cloud Platform Software Engineer at NVIDIA

Seattle, Washington, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, Cloud Computing, High-Performance ComputingIndustries

Requirements

BS in Computer Science, Information Systems, Computer Engineering or equivalent experience
Solid technical foundation in distributed computing and storage, including substantial experience with server systems, storage, I/O, networking, and system software
12+ years of platform engineering experience on large-scale production systems
Kubernetes and IaC expertise as an engineer
Ability to understand and communicate complex designs, distributed infrastructure, and requirements to peers, customers, and vendors
General shared storage knowledge such as NFS, LustreFS, GlusterFS, etc
Familiarity with system-level architecture, such as interconnects, memory hierarchy, interrupts, and memory-mapped IO
Ways to stand out
Proven experience in high performance computing, Deep Learning, and/or GPU accelerated computing domains
Large-scale distributed system, HPC, ML and Training experience with Slurm and Kubernetes
Deep knowledge of both software and hardware knowledge in HPC and ML infrastructure

Responsibilities

Build and design platforms for DGX Cloud services
Figure out how to take best from HPC and Kubernetes and help make the unified platform
Work within the team of software engineers and product people as well as engineering teams across all of NVIDIA on DGX Cloud AI Compute services
Write IaC code, work on Kubernetes, and help the team to design and implement release pipelines
Collaborate to understand how to make the best use of GitOps and Pipelines

Skills

Key technologies and capabilities for this role

KubernetesIaCGitOpsHPCDistributed ComputingStorageNetworkingSystem SoftwareRelease Pipelines

Questions & Answers

Common questions about this position

What experience level is required for this Senior Cloud Platform Software Engineer role?

The role requires 12+ years of platform engineering experience on large-scale production systems.

What are the key technical skills needed for this position?

Candidates need a solid foundation in distributed computing and storage, including server systems, storage, I/O, networking, and system software, plus Kubernetes and IaC expertise, general shared storage knowledge like NFS and LustreFS, and familiarity with system-level architecture.

What education is required for this role?

A BS in Computer Science, Information Systems, Computer Engineering or equivalent experience is required.

Is this a remote position or does it require office work?

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 position?

Proven experience in high performance computing, Deep Learning, GPU accelerated computing, large-scale distributed systems, HPC, ML and Training with Slurm and Kubernetes, and deep knowledge of software and hardware in HPC and ML infrastructure will help candidates stand out.

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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