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 @ 7
Go @ 4
Kubernetes @ 4
CI/CD @ 4
Distributed Systems @ 4
gRPC @ 4
IaaS @ 4
API @ 4
Cloud Computing @ 4
GPU @ 4
Deep Learning @ 4
Observability @ 6
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
We are looking for a Senior Software Engineer who sees the big picture of cloud computing and loves building cloud infrastructure. You will design and operate highly scalable cloud platform services that power GPU‑powered services such as GeForce NOW and NVIDIA's GPU cloud offerings. Your work will shape how AI, deep learning, and high‑end gaming are delivered from the cloud and will power NVIDIA's GPU‑accelerated data centers worldwide. You will play a key role in upstream communities such as Kubernetes and KubeVirt, adding features and integrations needed to support GeForce NOW and next‑generation NVIDIA platforms.
Responsibilities
- Design, implement, and operate cloud platform services that provide GPU‑accelerated IaaS on top of Kubernetes and KubeVirt.
- Develop and extend Kubernetes and KubeVirt components (e.g., operators/controllers, CRDs, device plugins) to support GeForce NOW and new NVIDIA hardware platforms.
- Drive the underlying technology stack: influence architecture, coding standards, observability, and deployment methodology for high‑scale, high‑availability services.
- Collaborate closely with product, hardware, and other engineering teams to deliver new capabilities end‑to‑end, including leading design discussions and aligning engineering leads on architecture and technology choices.
- Lead performance tuning, scalability improvements, and pervasive automation across the stack (provisioning, testing, deployment, operations).
- Own and document system and software architecture, designs, and implementation details for the services you build.
- Mentor engineers on the team and help foster a culture of engineering excellence, learning, and collaboration.
Requirements
- BS or MS in Computer Science or a related field (or equivalent experience).
- 6+ years of hands‑on experience building software and/or scalable cloud services.
- Significant experience building distributed systems or cloud‑scale services, including well‑designed APIs (e.g., REST/gRPC).
- Experience with cloud infrastructure: containers, Kubernetes, CI/CD pipelines, and production operations.
- Experience leading design reviews and influencing technical direction across teams, including communicating design documents, defending trade‑offs, and driving decisions with data.
- Proven skills developing in Go (GoLang), including working with Kubernetes/KubeVirt APIs and custom resources.
- Deep understanding in at least some of these areas: virtualization (KVM/QEMU/libvirt, KubeVirt), container orchestration, distributed systems, load balancing, security, or large‑scale multi‑tenant cloud platforms.
Ways to stand out
- Demonstrated upstream contributions to Kubernetes, KubeVirt, or related CNCF/open source projects (PRs, reviews, design proposals, or maintainer roles).
- Experience building Kubernetes device plugins or similar integrations for CPU/GPU/accelerator/network hardware.
- Familiarity with AI‑assisted development tools and a pragmatic approach to using them to improve quality and velocity.
Compensation & Other
- Base salary range: 184,000 USD - 287,500 USD (determined based on location, experience, and pay of employees in similar positions).
- You will also be eligible for equity and benefits.
- Applications for this job will be accepted at least until February 9, 2026.
- This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.