NVIDIA is advancing accelerated computing and artificial intelligence through technology that powers breakthroughs in graphics, robotics, and autonomous vehicles. Our private cloud team builds and operates infrastructure that supports software engineers across graphics, deep learning, autonomous vehicles, and Omniverse. The platform spans thousands of servers, processes millions of automated jobs each day, and manages petabytes of storage. Join us to solve distributed systems challenges, develop agentic infrastructure workflows, and improve the reliability and efficiency of services that accelerate engineering across NVIDIA.
What you’ll be doing:
- Design, build, and operate scalable cloud services for job execution, resource management, and storage.
- Solve infrastructure challenges across Kubernetes, job scheduling, multi-region services, and automated recovery.
- Develop agentic workflows that streamline infrastructure operations and reduce repetitive manual work.
- Build observability, monitoring, and remediation capabilities to improve platform reliability and diagnose production issues.
- Partner with engineering teams to understand customer needs and deliver solutions from concept through production.
- Drive capacity planning, performance optimization, and production readiness as the platform grows.
What we need to see:
- Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
- 8+ years of infrastructure development experience, including delivering scalable cloud solutions from concept to production.
- Strong object-oriented programming skills in Java or Go.
- Background in artificial intelligence, machine learning, and data analytics, with the ability to apply these techniques to infrastructure.
- Ability to diagnose complex distributed systems issues and drive root-cause resolution.
- Effective collaboration across engineering teams and time zones, with ownership of customer needs and production outcomes.
Ways to stand out from the crowd:
- A track record of operating large-scale distributed platforms and improving reliability, scalability, and operational efficiency.
- Hands-on work with Kubernetes, container orchestration, and multi-cluster or multi-region environments.
- Success building observability, alerting, and automated remediation systems that reduce operational toil.
- Expertise in capacity planning, performance tuning, and preparing rapidly growing platforms for production.
- Demonstrated ownership of ambiguous infrastructure challenges, from solution design through ongoing operation and continuous improvement.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- Bachelor's degree in Computer Science, Computer Engineering, or a related field, or equivalent experience
- 8+ years of infrastructure development experience delivering scalable cloud solutions from concept to production
- Strong object-oriented programming skills in Java or Go
- Background in artificial intelligence, machine learning, and data analytics, with the ability to apply these techniques to infrastructure
- Ability to diagnose complex distributed systems issues and drive root-cause resolution
- Effective collaboration across engineering teams and time zones, with ownership of customer needs and production outcomes
- Experience operating large-scale distributed platforms and improving reliability, scalability, and operational efficiency
- Hands-on experience with Kubernetes, container orchestration, and multi-cluster or multi-region environments
- Experience building observability, alerting, and automated remediation systems
- Expertise in capacity planning, performance tuning, and production readiness for rapidly growing platforms
- Ownership of ambiguous infrastructure challenges from solution design through ongoing operation and continuous improvement
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
