NVIDIA
ML Ops DSX Senior Engineer
$184K–$356K
US, CA, Santa Clara +2 · Senior · Full-time · Posted Oct 28, 2026
- Location
- US, CA, Santa Clara
US, Remote
US, WA, Seattle - Experience
- 8+ years in customer-facing technical roles such as Solutions Engineering, DevOps, Site Reliability, or ML Infrastructure Engineering.
- Education
- BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
About the job
Build and deploy AI workloads and MLOps solutions on NVIDIA and partner cloud platforms, while supporting customers and optimizing production performance.
What you'll do
- Develop and deploy AI solutions, including distributed training, inference optimization, and MLOps pipelines.
- Support strategic partners with production troubleshooting, platform guidance, and workload performance tuning.
- Deploy and manage workloads across cloud and data-center environments, and create implementation guides and runbooks.
What they ask for
- BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
- Strong expertise in Linux systems, distributed computing, Kubernetes, containers, and GPU scheduling.
- Production experience supporting large-scale AI/ML training and inference workloads.
- Programming skills in Python/Go and hands-on experience with PyTorch or TensorFlow.
Nice to have
- Experience with NVIDIA technologies including DGX systems, CUDA, NeMo, Triton, NIM, InfiniBand, or RoCE.
- Experience with NVIDIA Cloud Partners, hyperscale CSPs, MLOps, observability, GitOps, or infrastructure as code.
Pay
184,000 USD - 287,500 USD (base salary); 224,000 USD - 356,500 USD (base salary)
Tools
NCP, Neo Cloud, DGX Cloud, Kubernetes, Python, Go, PyTorch, TensorFlow
AI focus
Develop and operate AI workloads, including distributed training, inference optimization, and MLOps pipelines; tune large-scale training and inference performance.
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