NVIDIA
Principal AI and ML Infra Software Engineer, GPU Clusters
$272K–$431K
US, CA, Santa Clara +1 · Principal · Full-time · Posted Oct 14, 2026
- Location
- US, CA, Santa Clara
US, WA, Redmond - Experience
- 15+ years of demonstrated expertise in AI/ML and HPC tasks and systems.
- Education
- BS or similar background in Computer Science or a related area, or equivalent experience.
About the job
Leads improvements to GPU-cluster infrastructure so AI and ML research teams can run efficient, scalable training and research workloads.
What you'll do
- Identify infrastructure needs and researcher bottlenecks, then lead improvements and long-term roadmaps.
- Monitor and optimize infrastructure performance, availability, scalability, and resource use.
- Define researcher-efficiency measures and collaborate with researchers, data engineers, and DevOps teams on infrastructure improvements.
What they ask for
- 15+ years of demonstrated expertise in AI/ML and HPC tasks and systems.
- Hands-on experience with HPC-grade infrastructure and in-depth knowledge of accelerated computing, storage, scheduling and orchestration, networking, and containers.
- Experience supervising and improving distributed training operations using PyTorch, NeMo, or JAX, and understanding AI/ML workflows.
- Proficiency in Python, Go, and Bash; familiarity with cloud platforms and parallel computing frameworks and paradigms.
Pay
272,000 USD - 431,250 USD (base salary)
Tools
GPU, Lustre, GPFS, BeeGFS, Slurm, Kubernetes, PyTorch, NeMo
AI focus
Improves GPU-cluster infrastructure and distributed AI/ML training operations, supporting research workflows from data processing through training and inference.
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