DSX NVCRE Senior Engineer

NVIDIA is hiring a DSX NVCRE Senior Engineer in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

Builds AI ●●●● is how Level rates this role: the job is building AI systems.
Tools and skills the posting cites include vLLM and PyTorch.
Level classifies it as a senior role.
Level lists 2,700+ other open roles at NVIDIA.
The role was posted in the last few days.

AI in this role

vllmpytorch

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. NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and dedicated people in the world working for us.

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.

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.

How we rate this

DSX NVCRE Senior Engineer at NVIDIA rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

DSX NVCRE Senior Engineer is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $184k-$288k a year.
The role is based in US, CA, Santa Clara.
The job was posted on October 28, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

vLLMPyTorch

Questions you could be asked

What's a project where you used vLLM hands-on?
Walk me through how you've used PyTorch in your day-to-day work.
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: vLLM and PyTorch. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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