NVIDIA
Senior DGX Cloud AI Infrastructure Software Engineer
$184K–$356K
US, CA, Santa Clara +4 · Senior · Full-time · Posted Sep 29, 2026
- Location
- US, CA, Santa Clara
US, TX, Austin
US, OR, Remote
US, WA, Remote
US, WA, Redmond - Experience
- Minimum of 8+ years.
- Education
- Bachelor’s degree or higher in Computer Science or a related technical field (or equivalent experience).
About the job
Develops and maintains software infrastructure, tools, and APIs to improve the efficiency, resiliency, and reliability of large-scale AI training and inference systems.
What you'll do
- Build infrastructure software and tools for pre-training, post-training, and inference; optimize efficiency and resiliency.
- Co-design and implement APIs for NVIDIA’s resiliency stacks and enhance AI platform infrastructure.
- Define reliability metrics and investigate failures from the application level to the hardware level.
What they ask for
- 8+ years of experience developing software infrastructure for large-scale AI systems.
- Bachelor’s degree or higher in Computer Science or a related technical field, or equivalent experience.
- Experience building and scaling large-scale distributed systems and AI training and inference infrastructure services.
- Strong debugging and triage skills; experience with observability platforms and proficiency in Python, C/C++, or scripting languages.
Nice to have
- Experience with large-scale clusters, observability and telemetry stacks, or RDMA software stacks.
- Knowledge of PyTorch, TensorFlow, JAX, or Ray internals.
Pay
184,000 USD - 287,500 USD (base salary, Level 4); 224,000 USD - 356,500 USD (base salary, Level 5)
Tools
ELK, Prometheus, Loki, Python, C/C++, NCCL, IB verbs, ucx
AI focus
Develops infrastructure for AI pre-training, post-training, and inference, focused on efficiency, resiliency, and reliability.
Model-written summary · the original posting is authoritative