Senior Cloud Platform Software Engineer
@ NVIDIA

Santa Clara, CA
$300,000
On Site
Full Time
Posted 1 day ago

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Job Details

About the Role

NVIDIA is building the best cloud offering for AI workloads with its latest GPU technology, delivered as managed services under the DGX Cloud umbrella. As a Senior Cloud Platform Software Engineer, you will be a founding team member developing scalable, fault-tolerant cloud services for Artificial Intelligence and high-performance computing.

Key Responsibilities

  • Design and build platforms for DGX Cloud services.
  • Integrate HPC and Kubernetes for a unified platform.
  • Collaborate with software engineers, product teams, and cross-department engineering teams.
  • Write IaC code, work on Kubernetes, and design release pipelines.
  • Leverage GitOps and CI/CD pipelines.

What We Need To See

The ideal candidate holds a BS in Computer Science or equivalent and brings 12+ years of platform engineering experience, with strong distributed computing, networking, and storage expertise. Proficiency in Kubernetes, Infrastructure as Code, and understanding of system-level architecture are essential.

Ways To Stand Out

  • Experience in high performance computing, Deep Learning, or GPU accelerated computing.
  • Proven background in large-scale distributed systems using Slurm and Kubernetes.
  • Deep knowledge in both software and hardware aspects of HPC and ML infrastructures.

Compensation & Benefits

Your base salary is determined by location, experience, and equity/benefits. The base salary range is 224,000 USD - 356,500 USD.

Equal Opportunity

NVIDIA is committed to diverse work environment and equal opportunity employment. Applications accepted until September 22, 2025.

Key skills/competency

  • Cloud
  • AI
  • HPC
  • Kubernetes
  • IaC
  • Distributed Systems
  • Networking
  • Storage
  • GitOps
  • CICD
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How to Get Hired at NVIDIA

🎯 Tips for Getting Hired

  • Research NVIDIA's culture: Study their innovations, mission, and work ethics.
  • Customize your resume: Highlight cloud and Kubernetes expertise.
  • Network on LinkedIn: Connect with current NVIDIA employees.
  • Prepare technical details: Be ready to discuss IaC and distributed systems.

📝 Interview Preparation Advice

Technical Preparation

Review Kubernetes configurations and IaC practices.
Practice distributed systems design problems.
Study scaling and performance tuning techniques.
Refresh system architecture and networking fundamentals.

Behavioral Questions

Describe a collaboration challenge overcome.
Explain managing project deadlines under pressure.
Share a time for critical decision making.
Discuss conflict resolution within technical teams.

Frequently Asked Questions