We are developing advanced multi-rack, multi-tenant AI/ML datacenters with NVIDIA GB200, and upcoming GB300 GPUs. NVIDIA seeks a Senior Software Engineer for our CSP (Cloud Service Provider) Engagements team to focus on the cloud-native stack for datacenter products like GB200. In this role, You will define customer workflows, prototype stack enhancements, and debug the toughest Kubernetes + Slurm issues in multi-rack, multi-tenant AI datacenters. You'll tackle complex scheduling challenges across racks, tenants, and clouds as part of the CSP engagements team.
What you’ll be doing:
Perform deep-dive debugging of multi-rack, multi-tenant clusters: scheduler behavior, container runtime issues, device-plugin crashes, RDMA/IB fabric anomalies, etc.
Gather customer requirements and prototype feature extensions for Kubernetes operators, Slurm plugins, and custom micro-services that expose new GPU capabilities.
Drive joint architecture reviews and “whiteboard” sessions with CSP and internal platform teams; convert findings into RFCs and upstream pull requests.
Create reproducible testbeds (Helm/Ansible/Terraform) that mirror customer environments; automate validation and benchmark suites.
Deliver technical collateral-design docs, how-to guides, demo scripts-and present at customer on-sites, KubeCon, and SlurmUG.
Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation.
What we need to see:
Strong source-level expertise in Kubernetes internals (scheduler, CRI/CNI/CSI, operators) and Slurm (federation, power-save, plugins).
Hands-on experience integrating next-gen GPUs (Blackwell/GB200/GB300) or comparable accelerators into containerized clusters.
Proven track record debugging large-scale, cloud-native stacks across networking (RDMA/RoCE), storage, and control planes.
Customer-facing engineering or solutions-architect background: requirements gathering, PoC ownership, roadmap influence.
Familiarity with CI/CD (GitHub Actions, Tekton), observability (Prometheus, OpenTelemetry), and infrastructure-as-code.
Excellent communication-able to switch between deep technical detail and high-level business impact.
6+ years of professional software development experience in distributed systems (Go, Rust, C/C++ or Python for tooling).
BS or MS (or equivalent experience) in Computer Engineering, Computer Science, or related field.
Ways to stand out from the crowd:
Upstream contributions to Kubernetes, Slurm, Volcano, or similar projects.
Experience with GPU computing (CUDA), deep learning workloads
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard-working people in the world working for us. NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, hardworking and self-motivated, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.You will also be eligible for equity and benefits.
Top Skills
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.”
