About the role
What will you do at NVIDIA?
NVIDIA is looking for outstanding software engineers to help us expand our enterprise GPU management and monitoring tools.
In this role, you will
- work closely with the broader NVIDIA team to design and build cloud-native management agents, Kubernetes integrations, and end-to-end integration solutions that combine GPUs with the rest of the datacenter software management ecosystem. We are focused on supporting NVIDIA products across HPC, cloud, and enterprise on both bare metal and virtualized platforms as the role of GPUs in all of these environments expands. Your contributions will span many aspects of GPU system integration, including telemetry and metrics, health checks, diagnostics, configuration, and system management. These tools fill roles of both passive background monitoring and active online management with a core emphasis on operational transparency and seamless integration in customer environments. Your code will support single-node developer systems through large clusters with thousands of nodes.
- To succeed, you must have a strong Linux background, familiarity with modern cloud-native systems, and a proven work ethic. You will be expected to jump in quickly and provide valuable contributions from day one. This is a dynamic work environment with many exciting opportunities awaiting. NVIDIA GPUs are central to many hot enterprise, cloud, and datacenter trends. Come join us as we craft the future of accelerated computing and AI.
- What you'll be doing:
- Develop and maintain distributed, robust and scalable Go programs deployed to Kubernetes environments that manage large datacenters
- Develop and maintain user-space applications, containers, Go-bindings, and CLI tools.
- Enable GPU management integration with the state-of-the-art open-source ecosystem, including Kubernetes and Docker.
- Support internal and external users through bug fixes, documentation, and feature improvements.
- Maintain high-quality products through robust test coverage.
- What we need to see:
- BS or higher in Computer Science or equivalent experience. 5+ years of meaningful industry experience with a strong Go and Kubernetes development background
- User space development and debugging expertise in Linux environments
- Experience with APIs and interface design
- Outstanding written and verbal interpersonal skills. Business level English
- Strong motivation and commitment to learn new skills
- Ability to execute all aspects of the software development lifecycle. Ability to manage time in a fast, heavily multitasked environment
- Development experience with Rust, Python and/or C, C++. Development experience with distributed systems and concurrent applications, especially in a Kubernetes environment
- Experience developing and maintaining enterprise software. Experience deploying, managing, and debugging applications in a Kubernetes environment
- Ways to stand out from the crowd:
- Background with containers (e.g. Docker, OCI), orchestration frameworks, and logging/telemetry backends with Kubernetes monitoring stacks with tools such as Prometheus, Loki and Grafana
- Experience with modern UI development in React and Node.js or similar frameworks. Experience developing Kubernetes operators or Helm charts
- Experience with HPC job schedulers like Slurm or Run.AI Familiarity with Kubernetes internals. Exposure to GPU programming with CUDA. Experience with Jenkins and GitHub/GitLab CI/CD pipelines
- Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
- You will also be eligible for equity and benefits.
- Applications for this job will be accepted at least until August 15, 2026.
- 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.
Which skills does this role require?
Make your next move
Build a shortlist and prepare
Identify the requirements you can demonstrate, then choose examples from your work to discuss with the hiring team.
- Build a focused shortlist before you applyCompare role requirements with your experience and give each application a clear reason.
- Practice explaining your experience in an interviewRehearse your answers before meeting the hiring team.
Other roles to compare
Review the responsibilities and requirements before adding an opening to your shortlist.
Orchestration Workload Engineer - ACE - AI Factory
Roche · Kaiseraugst, Aargau, Switzerland
Analytics Sr Software Engineer (US Federal)
Workday · Reston, Virginia, United States
Staff/Principal AI Transformation Engineer
DiDi Autonomous Driving · San Jose, California, United States
AI Evaluations Engineer, US Decision Intelligence
Apple · Cupertino, California, United States
AI Outcome Customer Engineer, Forward Deployed Engineering
Google · Atlanta, Georgia, United States
Research Engineer, Responsible Frontier AI Research, DeepMind
Google · New York, New York, United States
Role information can change. Confirm current details on the original application page.
