Cloud Solutions Architect
@ NVIDIA

Hybrid
$190,000
Hybrid
Full Time
Posted 22 days ago

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Job Details

Overview

NVIDIA is seeking a passionate Cloud Solutions Architect to work on large-scale GPU infrastructure and AI Factory deployments. In this role, you will deploy resilient, telemetry-driven AI compute environments and collaborate with engineering teams.

What You'll Be Doing

  • Serve as a technical expert on NVIDIA AI Factory solutions and GPU infrastructure.
  • Collaborate with engineering teams for design wins and production deployments.
  • Advise clients, translate requirements, and optimize scalable workloads.
  • Develop robust tooling for observability and failure recovery.

What We Need To See

  • 2+ years in cloud infrastructure engineering or GPU cluster deployment.
  • BS in Computer Science, Engineering, Mathematics, Physics or equivalent.
  • Understanding of multi-node GPU clusters, networking and distributed storage.
  • Experience in infrastructure-as-code, automation, and configuration management.
  • A passion for machine learning, AI, and continuous learning.

Ways To Stand Out

  • Expertise in orchestration tools such as Slurm, Kubernetes, or Run:ai.
  • Knowledge of AI training instrumentation and distributed training frameworks.
  • Design telemetry systems and failure recovery mechanisms.
  • Experience with cloud-native solutions on AWS, Azure or Google Cloud.
  • Familiarity with high-performance networking and NVIDIA InfiniBand technologies.

Compensation & Benefits

Base salary is determined based on location and experience. Compensation packages include equity and attractive benefits.

Key Skills/Competency

Cloud, GPU, Infrastructure, AI, Observability, Telemetry, Automation, Kubernetes, AWS, Networking

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How to Get Hired at NVIDIA

🎯 Tips for Getting Hired

  • Customize your resume: Highlight cloud infrastructure and AI experience.
  • Showcase technical skills: Detail your GPU and automation projects.
  • Research NVIDIA culture: Study their mission and innovative projects.
  • Prepare for interviews: Practice explaining complex tech concepts simply.

📝 Interview Preparation Advice

Technical Preparation

Review GPU cluster architectures and protocols.
Practice infrastructure-as-code scripting.
Familiarize with Kubernetes and orchestration tools.
Study cloud-native deployment best practices.

Behavioral Questions

Describe a complex problem you solved.
How do you prioritize competing tasks?
Explain a project with client collaboration.
Discuss adapting to fast-paced changes.

Frequently Asked Questions