DSX NVCRE Senior Engineer

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,