2 days ago
Base Salary
$224k - $431k/yr
Responsibilities
- Drive the design, development, launch, and operation of AI infrastructure services, tools, and open-source projects.
- Plan and assign team work, mentor junior engineers, and review designs.
- Build resilient AI infrastructure on Kubernetes and Slurm for cloud, on-premises, customer, and NVIDIA training workloads.
- Develop APIs connecting telemetry, break/fix automation, checkpointing, and execution systems.
- Build job-submission systems that automatically restart long-running training jobs after infrastructure failures.
- Create agentic tools to identify training bottlenecks, diagnose failures, and recommend fixes.
- Release and improve open-source ML infrastructure components with customers and the broader community.
- Establish service support, monitoring, alerting, integration test gates, and on-call plans.
Requirements
- BS, MS, or PhD in Computer Science or a related field, or equivalent experience.
- 12+ years of experience and a proven record of taking large systems from design through production.
- Strong experience with Kubernetes and/or Slurm at scale.
- Hands-on experience with PyTorch, TensorFlow, JAX, or Ray.
- Strong understanding of NVIDIA GPUs and networking, including failure modes.
- Experience operating production services with monitoring, alerting, and on-call responsibilities.
- Experience with fault tolerance or checkpointing for large-scale distributed GPU training is preferred.
- Experience building LLM-based agents or AI tools for performance analysis or troubleshooting is preferred.
- Experience building external services or maintaining open-source ML infrastructure projects is preferred.
Benefits
- Eligible for equity and benefits.
- Applications will be accepted at least until November 10, 2026.
- This posting is for an existing vacancy.
Tech Stack
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.