Senior Systems Engineer: GPU-Accelerated Kubernetes & Containers

NVIDIA; New York (NY); On-site; USD 184,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Sr. Systems Software Engineer to design and build platform software for container runtimes and Kubernetes. You’ll contribute to Rust and Go based systems, distributed design, and performance-focused internals across the stack.

You’ll be part of a small team enabling GPUs in Kubernetes, collaborating with engineers across NVIDIA, and tackling challenging workload orchestration and reliability issues. Excellent communication and planning are essential.

Qualifications

• BS/MS in CS or related field (or equivalent experience)
• 8+ years of relevant work experience
• Expert-level knowledge in Go or Rust; strong data structures and algorithms
• Strong knowledge of Kubernetes and container tech
• Expert with Unix/Linux kernel internals
• Background in cloud computing and distributed design
• Understanding performance, security, reliability in distributed systems

Responsibilities

• Join a small, dynamic team advancing GPU-accelerated app development, deployment, and monitoring.
• Enable GPUs as first-class resources in container orchestrators like Kubernetes.
• Join core Cloud Native group enabling NVIDIA accelerators in the Kubernetes environment.
• Collaborate with NVIDIA engineers to ensure seamless end-to-end software integration.
• Multitask across tracks to address evolving priorities efficiently.

Skills

Go

Rust

Kubernetes

Systems programming

Unix/Linux

Cloud computing

Distributed systems

Performance

Education

BS/MS in Computer Science

Tools

Kata Containers

Linux

Job description

NVIDIA is seeking a Sr. Systems Software Engineer to design and build platform software for container runtimes and Kubernetes. You’ll contribute to Rust and Go based systems, distributed design, and performance-focused internals across the stack.

You’ll be part of a small team enabling GPUs in Kubernetes, collaborating with engineers across NVIDIA, and tackling challenging workload orchestration and reliability issues. Excellent communication and planning are essential.