Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
Deep Learning
Distributed Systems @ 6
Go @ 7
Java @ 7
Kubernetes @ 4
Machine Learning @ 6
Observability @ 4
Performance Optimization
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA's 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. The role focuses on solving distributed systems challenges, developing agentic infrastructure workflows, and improving the reliability and efficiency of services that accelerate engineering across NVIDIA.
Responsibilities
- 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.
Requirements
- 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.
Preferred Qualifications
- Track record of 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 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.
Compensation and Benefits
- Base salary range of $184,000–$287,500 USD for Level 4.
- Base salary range of $224,000–$356,500 USD for Level 5.
- Base salary is determined based on location, experience, and the pay of employees in similar positions.
- Eligible for equity and benefits.
- NVIDIA offers a comprehensive benefits package.
Applications will be accepted at least until October 17, 2026. NVIDIA uses AI tools in its recruiting processes and is committed to fostering an inclusive work environment and providing equal employment opportunities.
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