Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 4
Go @ 4
Kubernetes @ 7
Linux @ 4
Python @ 4
Java @ 4
Algorithms @ 7
ArgoCD @ 7
Data Structures @ 7
Distributed Systems @ 4
Bash @ 4
gRPC @ 4
Rust @ 4
HTTP @ 4
GPU @ 4
AI @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Today, we’re tapping into the unlimited potential of AI to define the next era of computing. NVIDIA Cloud Functions (NVCF) is an open-source platform that links workloads to GPUs, letting 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 so endpoints can scale repeatably, whether hosted on-prem or in the cloud.
Responsibilities
- Improve the performance, reliability, and scaling behavior of a system that routes AI workloads onto distributed GPU fleets.
- Design and ship services in Java, Go, and Rust, building in the open on a public repository where commits, design proposals, and reviews are visible to the community.
- Automate and optimize build, test, integration, and release processes for cloud-native environments.
- Partner with engineering teams across NVIDIA so the platform integrates with adjacent NVIDIA technologies (KAI Scheduler, NVIDIA NIM, Grove, Dynamo).
- Steward an open-source project: triage community issues and pull requests and write documentation contributors can build on.
Requirements
- Bachelor’s or Master’s Degree in Computer Science or equivalent experience.
- 3+ years of hands-on software engineering experience.
- Expert-level knowledge in a systems programming language (Go, C, Rust) and strong 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 and ArgoCD.
- Expertise in a scripting language (Bash, Python) and knowledge and experience working with system internals of Unix/Unix-like kernels (Linux).
- Understanding of performance, security, and reliability concerns in complex distributed systems.
Ways to stand out
- Background with pub-sub models and message queues.
- Experience optimizing for high-throughput network paths and working knowledge of unary vs streaming and bidirectional protocols across HTTP/2 and gRPC.
- Experience developing Kubernetes Custom Resources and Operators deployed in Cloud Service Providers.
Compensation & Other Details
- Base salary range (annual) provided by location/level:
- Level 3: 152,000 USD - 241,500 USD
- Level 4: 184,000 USD - 287,500 USD
- Eligible for equity and benefits.
- Applications accepted at least until July 11, 2026.
- NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.