NVIDIA’s DGX Cloud team builds the infrastructure behind large-scale AI training for NVIDIA’s own training workloads and for our customers. We build services, tools and open-source software that make ML workloads more efficient and resilient.
We’re looking for a Senior Software Engineer for the NVIDIA Recovery and Resilience team. You’ll own our AI infrastructure services, tools and open-source projects to support resilient and efficient training from design through production. You’ll also mentor engineers and decide how the team runs what it builds.
What You Will Be Doing:
- Drive the design, build, launch and operation of our services, tools and open-source projects.
- Plan and assign the team’s work, mentor junior engineers and review designs.
- Build resilient AI infrastructure on Kubernetes and Slurm for NVIDIA’s own training workloads and customer workloads. This includes supercomputers at major cloud providers and on-premises clusters.
- Build APIs that connect to NVIDIA’s resiliency systems: telemetry, break/fix automation, and checkpoint and execution systems.
- Build a job submission layer that hides infrastructure failures from users and restarts long-running training jobs automatically.
- Build agentic tools that help customers improve training efficiency by finding bottlenecks, diagnosing failures and recommending fixes.
- Drive our open-source work. Release components so customers and the community can use them, and work with them to improve those components.
- Set up how the team runs its services: support, monitoring, alerts, CI/CD, integration test gates and on-call plans.
What We Need To See:
- BS, MS or PhD in Computer Science or a related field (or equivalent experience), plus 12+ years of experience.
- Proven experience who has taken 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 how they fail.
- Experience running production services, including CI/CD, monitoring, alerting and on-call.
Ways to Stand Out from the Crowd:
- Hands-on experience with fault tolerance or checkpointing for large-scale distributed training on GPU supercomputers.
- Demonstrated experience building LLM-based agents or AI tools for performance analysis or troubleshooting.
- Background in building external services or maintaining open-source projects in ML infrastructure.
224,000 USD – 356,500 USD for Level 5; and 272,000 USD – 431,250 USD for Level 6.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- BS, MS, or PhD in Computer Science or a related field, or equivalent experience
- 12+ years of professional experience
- Experience 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 behavior
- Experience running production services, including CI/CD, monitoring, alerting, and on-call operations
- Experience with fault tolerance or checkpointing for large-scale distributed training on GPU supercomputers
- Experience building LLM-based agents or AI tools for performance analysis or troubleshooting
- Experience building external services or maintaining open-source ML infrastructure projects
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
-
Equity Value & Accessibility — Feedback suggests equity grants, stock options/RSUs, and a discounted ESPP materially boost total compensation and can deliver significant wealth-building when the stock performs well.
-
Healthcare Strength — Feedback suggests medical, dental, and vision plans with in-network preventive care at 100%, telehealth, and concierge-style support are comprehensive and valued.
-
Parental & Family Support — Feedback suggests up to 22 weeks fully paid parental leave, fertility coverage, and adoption/surrogacy reimbursement provide strong family-focused benefits.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
.jpeg)
