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.
10+ 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.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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
- 6+ years of professional software development experience in distributed systems
- Strong expertise in Kubernetes and Slurm
- Hands-on experience with next-gen GPUs and containerized clusters
- Customer-facing engineering or solutions-architect background
- Familiarity with CI/CD and infrastructure-as-code
- BS or MS in Computer Engineering, Computer Science, or related field
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.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
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.”
