12 days ago
Base Salary
$184k - $357k/yr
Responsibilities
- Perform deep-dive debugging of multi-rack, multi-tenant clusters, including scheduler behavior, container runtimes, device plugins, and RDMA/InfiniBand fabric issues.
- Gather customer requirements and prototype extensions for Kubernetes operators, Slurm plugins, and microservices exposing GPU capabilities.
- Lead architecture reviews and whiteboard sessions with CSP and internal platform teams, converting findings into RFCs and upstream pull requests.
- Create Helm, Ansible, and Terraform testbeds that mirror customer environments and automate validation and benchmark suites.
- Create technical collateral, design documents, how-to guides, and demo scripts, and present at customer sites, KubeCon, and SlurmUG.
- Collaborate with account executives, field application engineers, and solution architects to deliver integrated customer solutions and documentation.
Requirements
- Strong source-level expertise in Kubernetes internals, including the scheduler, CRI, CNI, CSI, and operators.
- Strong expertise with Slurm, including federation, power-save, and plugins.
- Hands-on experience integrating Blackwell, GB200, GB300, or comparable accelerators into containerized clusters.
- Experience debugging large-scale cloud-native stacks across networking, storage, and control planes, including RDMA/RoCE.
- Customer-facing engineering or solutions-architecture experience involving requirements gathering, proof-of-concept ownership, and roadmap influence.
- Familiarity with GitHub Actions, Tekton, Prometheus, OpenTelemetry, and infrastructure-as-code.
- Excellent communication skills for translating deep technical details into high-level business impact.
- At least 10 years of professional software development experience in distributed systems using Go, Rust, C, C++, or Python for tooling.
- BS or MS in Computer Engineering, Computer Science, or a related field, or equivalent experience.
- Preferred qualifications include upstream contributions to Kubernetes, Slurm, Volcano, or similar projects, plus GPU computing and deep-learning workload experience.
Benefits
- Base salary ranges from $184,000 to $287,500 for Level 4 and from $224,000 to $356,500 for Level 5, depending on location and experience.
- Eligible for equity and benefits.
- Applications are accepted at least until October 14, 2026.
- This posting is for an existing vacancy.
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.