DSX NVCRE Senior Engineer

2100 NVIDIA USA; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Job summary

NVIDIA Corporation is seeking a Senior Software Engineer to join the DSX team. You will build tooling to verify AI infrastructure readiness for production, focusing on cluster readiness, certification, and evidence generation across Kubernetes and Slurm.

You will design and implement controllers, CLIs, and integrations, and contribute to open-source components while collaborating with internal and cloud partner teams.

Qualifications

• BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or related field, or equivalent experience.
• 8+ years of software engineering experience in large-scale compute/cloud/HPC environments.
• Strong programming in Go and Python with production services experience.
• Deep familiarity with Linux, containers, and Kubernetes; writing operators/controllers.
• Knowledge of HPC schedulers like Slurm and GPU cluster fundamentals (drivers, NCCL, InfiniBand/ RoCE).
• Experience benchmarking or validating distributed systems with rigorous measurement/traceability.
• Ability to drive complex investigations to root cause and communicate findings clearly.

Responsibilities

• Shape the future of cluster validation by building repeatable, verifiable software.
• Develop cluster readiness and certification tooling in Go and Python for Kubernetes and Slurm.
• Create benchmarks and workloads across compute, training, inference, and diagnostics.
• Develop provenance pipelines that capture execution details and produce auditable results.
• Integrate with new GPU platforms, schedulers, and fabrics from bring-up to multi-node validation.
• Collaborate with platform, networking, and cloud teams and contribute to open-source projects.

Skills

Go

Python

Linux

Kubernetes

Slurm

NCCL

DCGM

Education

BS/MS/PhD in CS/EE or related field

Tools

Kubernetes

Slurm

NCCL

DCGM

Job description

NVIDIA is seeking a Senior Software Engineer

to join our DSX team to build and operate the tooling that verifies AI infrastructure is ready for production. You will work on cluster readiness and certification software, including the open-source Cluster Readiness Engine, that validates GPU clusters across Kubernetes and Slurm, measures real training and inference performance, and produces evidence customers and partners can trust. We partner with the world's most innovative AI companies and cloud providers to make sure their infrastructure performs as designed before their most important workloads land on it.

What you will be doing:

• Shape the Future of Validation. Design and build the systems that turn cluster validation from a manual exercise into repeatable, verifiable software. Your work will directly shape how NVIDIA and its partners qualify new GPU platforms and deployments.
• Core Development. Design and implement cluster readiness and certification tooling in Go and Python that runs on Kubernetes and Slurm, including controllers, operators, CLIs, and scheduler integrations.
• Benchmarking & Workloads. Build a catalog of benchmarks and real workloads spanning communication (NCCL), compute, storage, diagnostics, training, inference, reliability, and security, with per-architecture expectations and clear pass/fail criteria.
• Data Provenance. Develop provenance and evidence pipelines that capture what actually ran, where it ran, and under which configuration, and that produce signed, auditable results.
• Platform Integration. Bring new GPU platforms, schedulers, and fabrics under test, from first bring-up on a single node through multi-node validation on production clusters.
• Cross-functional Collaboration. Collaborate with internal platform, networking, and solutions teams and with cloud partners to root-cause performance and correctness gaps found by the tooling, and feed fixes back into platforms and reference architectures.
• Open Source Contribution. Contribute to the open-source Cluster Readiness Engine and related projects, including design documents, documentation, and reviews.
• Technical Authorship. Author design documents, runbooks, and operational guides that codify how clusters are validated and how results are interpreted.

What we need to see:

• BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
• 8+ years of software engineering experience building infrastructure or systems software, ideally for large-scale compute, cloud, or HPC environments.
• Strong programming skills in Go and Python, with experience shipping production-quality services, controllers, or command-line tools.
• Deep familiarity with Linux systems, containers, and Kubernetes, including writing operators or controllers against the Kubernetes API.
• Working knowledge of HPC schedulers such as Slurm and of GPU cluster fundamentals: drivers, NCCL, InfiniBand or RoCE fabrics, and GPU health tooling such as DCGM.
• Experience benchmarking or validating distributed systems, with a rigorous approach to measurement, reproducibility, and evidence.
• Demonstrated ability to drive complex technical investigations to root cause and to communicate findings clearly to engineering and leadership audiences.

Ways to stand out from the crowd:

• Hands-on experience running or tuning large-scale distributed training or inference workloads with frameworks such as PyTorch, Megatron, NeMo, vLLM, SGLang, or TensorRT-LLM.
• Experience with the NVIDIA ecosystem, including DGX systems, GB200/GB300 platforms, CUDA, NVLink and NVSwitch fabrics, and NVIDIA networking.
• Prior contributions to open-source infrastructure projects, especially Kubernetes operators, scheduler plugins, or benchmarking frameworks.
• Background in software supply-chain security, attestation, or signed artifacts, and in building audit-grade evidence into systems.
• Familiarity with observability stacks (Prometheus, Grafana, OpenTelemetry), GitOps workflows, and infrastructure as code for GPU clusters.

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization.

The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars.

Pay and Benefits

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until November 1, 2026.

Recruitment Process

NVIDIA uses AI tools in its recruiting processes.

Equal Opportunity Employer

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.

About NVIDIA

NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.