[Hiring] Senior Systems Software Engineer @NVIDIA

Role Description

We are seeking a Senior Systems Software Engineer to join our team. You will focus on improving the performance, reliability, and scaling behavior of a system that routes AI workloads onto distributed GPU fleets. You will work on a polyglot platform that is now fully open source, with both control plane and edge deployments. The work suits someone with deep experience in systems performance, distributed systems, and Kubernetes-based runtimes.

What you will be doing:

• Working in a distributed team that explores innovative ways to make GPU- and DPU-accelerated applications easier to develop, deploy, and monitor on the latest NVIDIA hardware.
• Designing and shipping services in Java, Go, and Rust, building in the open on a public repository where your commits, design proposals, and reviews are transparent to the community.
• Automating and optimizing build, test, integration, and release processes for cloud native.
• Partnering with engineering teams across NVIDIA so the platform integrates with adjacent NVIDIA technologies, including the KAI Scheduler, NVIDIA NIM, Grove, and Dynamo.
• Helping steward an open-source project by triaging community issues and pull requests and writing documentation for contributors.

Qualifications

• Bachelor’s or Master’s Degree in Computer Science or equivalent experience.
• 3+ years of hands-on software engineering.
• Expert-level knowledge in a systems programming language (Go, C, Rust) and a proven understanding of Data Structures, Algorithms, and Distributed Software Architecture.
• Strong understanding of container orchestration systems (Kubernetes) and container technologies with hands-on automation experience in continuous integration frameworks like GitLab & ArgoCD.
• Expertise in a scripting language (Bash, Python) and knowledge and experience working with the system internals of Unix/Unix-like kernels such as Linux.
• Understanding of performance, security, and reliability in complex distributed systems.

Requirements

• Background with pub-sub models and message queues.
• Experience optimizing for high-throughput network paths, with a working understanding of unary versus streaming and bidirectional protocols across HTTP/2 and gRPC.
• Experience with developing Kubernetes Custom Resources and Operators deployed in Cloud Service Providers.

Benefits

• Competitive salaries.
• Generous benefits package.