Senior Systems Software Engineer - NV Cloud Functions

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. We are looking for engineers who want to learn and grow. Expect to be challenged in an environment with rapidly shifting priorities, where insight, focus, and execution are key.

What you will be doing:

• You’ll be 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 and greatest NVIDIA hardware.
• Design and ship 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.
• Work on automating and optimizing build, test, integration, and release processes for cloud native.
• Partner with engineering teams across NVIDIA so the platform integrates with adjacent NVIDIA technologies, including the KAI Scheduler, NVIDIA NIM, Grove, and Dynamo.
• Help steward an open-source project. You will triage community issues and pull requests and write docs contributors can build on.

• 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.

Ways to stand out from the crowd:

• 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

4.24.2 out of 5 stars 2788 San Tomas Expressway, Santa Clara, CA 95051 $152,000 - $287,500 a year - Full-time, With competitive salaries and a generous benefits package, NVIDIA is considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking individuals in the industry working for us. Due to unprecedented growth, our exclusive engineering teams are expanding rapidly. If you’re a creative and autonomous engineer with a genuine passion for technology, 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 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA Cloud Functions (NVCF) is an open-source platform that links workloads to GPUs. It lets teams deploy, manage, and serve GPU-accelerated, containerized applications across regions and clusters worldwide. The platform routes inference, streaming, and batch jobs across decentralized GPU clusters. This allows endpoints to scale repeatably, whether hosted on-prem or in the cloud.