Principal Software Engineer, Distributed Systems Engineer - DGX Cloud

at Nvidia

USD 272,000-431,200 per year

SENIOR

✅ On-site

Tech Stack
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3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

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AI @ 4 API @ 4 Algorithms @ 4 Communication @ 7 Data Structures @ 4 Deep Learning Distributed Systems @ 6 GPU @ 4 Go @ 4 Hiring @ 4 Kubernetes @ 4 Mathematics @ 4 Python @ 4 Slurm @ 7

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 to support a variety of AI workloads. You will work on custom Kubernetes software for GPU resource scheduling, monitoring, health management, and distributed systems reliability.

NVIDIA develops visual computing and GPU deep learning technologies for applications including video games, movie production, product design, medical diagnosis, scientific research, and AI computing.

Responsibilities

Work as part of the DGX Cloud team responsible for production systems supporting large-scale GPU clusters and AI workloads.
Develop custom software related to scheduling GPU resources on Kubernetes.
Implement monitoring and health management capabilities to improve 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 well-defined incident management process.

Requirements

Significant software engineering experience with Kubernetes, including cluster operations, operator development, node health monitoring, and GPU resource scheduling.
Direct experience in a software engineering role within a highly technical organization, with demonstrable impact from your work.
Experience developing software with Kubernetes APIs and frameworks, beyond merely operating a cluster.
Strong communication skills and the ability to work with multifunctional teams, principals, and architects across organizational boundaries and geographies.
15 or more 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 discipline, or equivalent experience.
Technical 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.

Benefits

Equity and benefits are provided.
NVIDIA is committed to an inclusive work environment and is an equal opportunity employer.

Applications will be accepted at least until October 3, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.