Senior Software Engineer, Distributed Systems Engineer - DGX Cloud

at Nvidia

USD 152,000-287,500 per year

SENIOR

✅ On-site

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 @ 4 API @ 4 Algorithms @ 4 Communication @ 7 Data Structures @ 4 Distributed Systems @ 7 GPU Go @ 4 Hiring @ 4 Kubernetes @ 4 Mathematics @ 4 Python @ 4 Slurm @ 7 Software Development @ 4

Details

NVIDIA is hiring experienced software engineers with Kubernetes experience to help scale its AI infrastructure. The role focuses on building and operating production systems that enable large-scale GPU clusters for AI workloads, including custom software for GPU resource scheduling on Kubernetes.

NVIDIA seeks creative, passionate engineers with a strong execution bias who are interested in Kubernetes, GPUs, distributed systems, and reliable infrastructure.

Responsibilities

Contribute to the DGX Cloud team responsible for production systems that enable large-scale GPU clusters for a variety of AI workloads.
Develop custom software related to scheduling GPU resources on Kubernetes.
Implement monitoring and health management capabilities for the reliability, availability, and scalability of GPU assets.
Work with data streams from GPU hardware diagnostics, cluster telemetry, and network telemetry.
Collaborate with teams across NVIDIA to ensure production AI clusters operate reliably, consistently, and with maximum performance.
Evaluate system failures and improve services through a defined incident management process.

Requirements

Direct experience in a software engineering role within a highly technical organization, with demonstrable impact from previous work.
Software development experience with Kubernetes APIs and frameworks, beyond simply operating a cluster.
Strong communication skills and the ability to work with multifunctional teams, principals, and architects across organizational boundaries and geographies.
At least 5 years of experience in a similar role and experience with large-scale production systems.
Knowledge of common software engineering principles, tools, and techniques.
A bachelor's degree in Computer Science, Engineering, Physics, Mathematics, or a comparable field, or equivalent experience.
Knowledge of a systems programming language such as Go or Python.
Solid understanding of data structures and algorithms.

Preferred Qualifications

Technical competency in managing and automating large-scale distributed systems independently of cloud providers.
Advanced hands-on experience and deep understanding of cluster management systems, including Kubernetes, Slurm, and Bright Cluster Manager.
Proven operational excellence in maintaining reliable and performant AI infrastructure.

Compensation and Benefits

The base salary depends on location, experience, and the pay of employees in similar positions. The base salary range is USD 152,000–241,500 for Level 3 and USD 184,000–287,500 for Level 4. The role also includes eligibility for equity and benefits.

Applications will be accepted at least until October 2, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.