Role at a glance
- Salary
- $184K – $356.5K/yr
- Location
- 5 Locations, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 10+ years of professional software development experience in distributed systems
- Education
- BS or MS (or equivalent experience) in Computer Engineering, Computer Science, or related field
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Role Summary
The Senior Software Engineer joins NVIDIA’s CSP Engagements team to develop and extend the cloud-native stack for multi-rack, multi-tenant AI/ML datacenter products such as GB200 and GB300. The role works with cloud service providers and internal platform teams to address Kubernetes and Slurm challenges, prototype capabilities, and deliver integrated customer solutions.
What You'll Do
- Perform deep-dive debugging of multi-rack, multi-tenant clusters, including scheduler behavior, container runtimes, device plugins, and...
- Gather customer requirements and prototype feature extensions for Kubernetes operators, Slurm plugins, and custom micro-services
- Drive architecture reviews and whiteboard sessions with CSP and internal platform teams, converting findings into RFCs and upstream pull...
- Create reproducible testbeds using Helm, Ansible, and Terraform, and automate validation and benchmark suites
- Deliver technical collateral, design documents, how-to guides, and 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
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Strong source-level expertise in Kubernetes internals and Slurm; hands-on experience integrating next-gen GPUs or comparable accelerators into containerized clusters; experience debugging large-scale cloud-native stacks across networking, storage, and control planes; customer-facing engineering or solutions-architect background; familiarity with CI/CD, observability, and infrastructure-as-code; excellent communication; 10+ years of professional software development experience in distributed systems.
Required
- Strong source-level expertise in Kubernetes internals (scheduler, CRI/CNI/CSI, operators)
- Strong source-level expertise in 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
- 10+ years of professional software development experience in distributed systems (Go, Rust, C/C++ or Python for tooling)
Preferred
- Upstream contributions to Kubernetes, Slurm, Volcano, or similar projects
- Experience with GPU computing (CUDA), deep learning workloads
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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 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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.