2 days ago
Base Salary
$152k - $288k/yr
Responsibilities
- Develop custom software for scheduling GPU resources on Kubernetes.
- Build monitoring and health management capabilities for GPU assets and clusters.
- Use GPU diagnostics, cluster telemetry, and network telemetry to improve reliability, availability, and scalability.
- Evaluate system failures and improve services through an incident management process.
- Coordinate with cross-functional teams across NVIDIA to maintain reliable and high-performance production AI clusters.
- Manage and automate large-scale distributed systems independent of cloud providers.
Requirements
- 5+ years of experience in a similar software engineering role and experience with large-scale production systems.
- Direct software development experience with Kubernetes APIs and frameworks, beyond operating Kubernetes clusters.
- A BS in Computer Science, Engineering, Physics, Mathematics, or a comparable degree, or equivalent experience.
- Proficiency in a systems programming language such as Go or Python.
- Strong understanding of data structures and algorithms.
- Demonstrated impact in a highly technical organization and ability to collaborate across teams and geographies.
- Preferred experience with Kubernetes, Slurm, Bright Cluster Manager, and reliable large-scale AI infrastructure.
Benefits
- Eligible for equity and benefits.
- Base salary is listed for Level 3 and Level 4 roles, with the range determined by location, experience, and comparable employee pay.
- Applications are accepted at least until October 2, 2026.
Tech Stack
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.